Evidence map›Paper›PMID 26614710›Full record

ArticleThe oncologist2016

Cost-Utility of a Prognostic Test Guiding Adjuvant Chemotherapy Decisions in Early-Stage Non-Small Cell Lung Cancer.

David D Stenehjem, Brandon K Bellows, Kraig M Yager, Joshua Jones, Rajesh Kaldate, Uwe Siebert, Diana I Brixner

Abstract read
In one paragraph

Article in The oncologist, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. A Preliminary Study of Microbiota Diversity in Saliva and Bronchoalveolar Lavage Fluid from Patients with Primary Bronchogenic Carcinoma.Medical science monitor : international medical journal of experimental and clinical research · 2019
    Article
  7. Review
  8. Article
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

7 authors.

David D StenehjemDepartment of Pharmacotherapy, Pharmacotherapy Outcomes Research Center, College of Pharmacy, University of Utah, Salt Lake City, Utah, USA Huntsman Cancer Institute, University of Utah Hospitals & Clinics, Salt Lake City, Utah, USA David.stenehjem@hsc.utah.edu.
Brandon K BellowsDepartment of Pharmacotherapy, Pharmacotherapy Outcomes Research Center, College of Pharmacy, University of Utah, Salt Lake City, Utah, USA SelectHealth, Salt Lake City, Utah, USA.
Kraig M YagerMyriad Genetics, Inc., Salt Lake City, Utah, USA.
Joshua JonesMyriad Genetics, Inc., Salt Lake City, Utah, USA.
Rajesh KaldateMyriad Genetics, Inc., Salt Lake City, Utah, USA.
Uwe SiebertDepartment of Public Health, Health Services Research and Health Technology Assessment, University for Health Sciences, Medical Informatics and Technology, Tyrol, Austria Area 4 Health Technology Assessment and Bioinformatics, Oncotyrol Center for Personalized Cancer Medicine, Innsbruck, Austria Department of Health Policy and Management, Center for Health Decision Science, Harvard School of Public Health, Boston, Massachusetts, USA Cardiovascular Research Program, Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Diana I BrixnerDepartment of Pharmacotherapy, Pharmacotherapy Outcomes Research Center, College of Pharmacy, University of Utah, Salt Lake City, Utah, USA Program in Personalized Health, University of Utah, Salt Lake City, Utah, USA Department of Public Health, Health Services Research and Health Technology Assessment, University for Health Sciences, Medical Informatics and Technology, Tyrol, Austria Area 4 Health Technology Assessment and Bioinformatics, Oncotyrol Center for Personalized Cancer Medicine, Innsbruck, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA prognostic test was developed to guide adjuvant chemotherapy (ACT) decisions in early-stage non-small cell lung cancer (NSCLC) adenocarcinomas. The objective of this study was to compare the cost-utility of the prognostic test to the current standard of care (SoC) in patients with early-stage NSCLC. MATERIALS AND

methodsLifetime costs (2014 U.S. dollars) and effectiveness (quality-adjusted life-years [QALYs]) of ACT treatment decisions were examined using a Markov microsimulation model from a U.S. third-party payer perspective. Cancer stage distribution and probability of receiving ACT with the SoC were based on data from an academic cancer center. The probability of receiving ACT with the prognostic test was estimated from a physician survey. Risk classification was based on the 5-year predicted NSCLC-related mortality. Treatment benefit with ACT was based on the prognostic score. Discounting at a 3% annual rate was applied to costs and QALYs. Deterministic one-way and probabilistic sensitivity analyses examined parameter uncertainty.

resultsLifetime costs and effectiveness were $137,403 and 5.45 QALYs with the prognostic test and $127,359 and 5.17 QALYs with the SoC. The resulting incremental cost-effectiveness ratio for the prognostic test versus the SoC was $35,867/QALY gained. One-way sensitivity analyses indicated the model was most sensitive to the utility of patients without recurrence after ACT and the ACT treatment benefit. Probabilistic sensitivity analysis indicated the prognostic test was cost-effective in 65.5% of simulations at a willingness to pay of $50,000/QALY.

conclusionThe study suggests using a prognostic test to guide ACT decisions in early-stage NSCLC is potentially cost-effective compared with using the SoC based on globally accepted willingness-to-pay thresholds. IMPLICATIONS FOR PRACTICE: Providing prognostic information to decision makers may help some patients with high-risk early stage non-small cell lung cancer receive appropriate adjuvant chemotherapy while avoiding the associated toxicities and costs in patients with low-risk disease. This study used an economic model to assess the effectiveness and costs associated with using a prognostic test to guide adjuvant chemotherapy decisions compared with the current standard of care in patients with non-small cell lung cancer. When compared with current standard care, the prognostic test was potentially cost effective at commonly accepted thresholds in the U.S. This study can be used to help inform decision makers who are considering using prognostic tests.

Indexed as

Cost-Benefit AnalysisQuality-Adjusted Life YearsCarcinoma, Non-Small-Cell LungChemotherapy, AdjuvantHumansModels, EconomicNeoplasm Recurrence, LocalNeoplasm StagingPrognosisCost-effectiveness analysisCost-utility analysisEconomic analysisNon-small cell lung cancerPrognostic test

Identifiers

PMID26614710
PMCPMC4746079

What OpenQuestion holds

Textmetadata
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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.