The premarket assessment of the cost-effectiveness of a predictive technology “Straticyte™” for the early detection of oral cancer: a decision analytic model

Abstract Introduction Approximately half of oral cancers are detected in advanced stages. The current gold standard is histopathological assessment of biopsied tissue, which is subjective and dependent on expertise. Straticyte™, a novel prognostic tool at the pre-market stage, that more accurately i...

Full description

Bibliographic Details
Main Authors: S. Khoudigian-Sinani, G. Blackhouse, M. Levine, L. Thabane, D. O’Reilly
Format: Article
Language:English
Published: BMC 2017-10-01
Series:Health Economics Review
Subjects:
Online Access:http://link.springer.com/article/10.1186/s13561-017-0170-6
id doaj-cfa6e173360f48fda0637f58621fae52
record_format Article
spelling doaj-cfa6e173360f48fda0637f58621fae522020-11-25T00:40:27ZengBMCHealth Economics Review2191-19912017-10-01711910.1186/s13561-017-0170-6The premarket assessment of the cost-effectiveness of a predictive technology “Straticyte™” for the early detection of oral cancer: a decision analytic modelS. Khoudigian-Sinani0G. Blackhouse1M. Levine2L. Thabane3D. O’Reilly4Department of Health Research, Methods, Evidence and Impact, Faculty of Health Sciences, McMaster UniversityDepartment of Health Research, Methods, Evidence and Impact, Faculty of Health Sciences, McMaster UniversityDepartment of Health Research, Methods, Evidence and Impact, Faculty of Health Sciences, McMaster UniversityDepartment of Health Research, Methods, Evidence and Impact, Faculty of Health Sciences, McMaster UniversityDepartment of Health Research, Methods, Evidence and Impact, Faculty of Health Sciences, McMaster UniversityAbstract Introduction Approximately half of oral cancers are detected in advanced stages. The current gold standard is histopathological assessment of biopsied tissue, which is subjective and dependent on expertise. Straticyte™, a novel prognostic tool at the pre-market stage, that more accurately identifies patients at high risk for oral cancer than histopathology alone. This study conducts an early cost-effectiveness analysis (CEA) of Straticyte™ and histopathology versus histopathology alone for oral cancer diagnosis in adult patients. Methods A decision-analytic model was constructed after narrowing the scope of Straticyte™, and defining application paths. Data was gathered using the belief elicitation method, and systematic review and meta-analysis. The early CEA was conducted from private-payer and patient perspectives, capturing both direct and indirect costs over a five-year time horizon. One-way and probabilistic sensitivity analyses were conducted to investigate uncertainty. Results Compared to histopathology alone, histopathology with Straticyte™ was the dominant strategy, resulting in fewer cancer cases (31 versus 36 per 100 patients) and lower total costs per cancer case avoided (3,360 versus 3,553). This remained robust when Straticyte™ was applied to moderate and mild cases, but became slightly more expensive but still more effective than histopathology alone when Straticyte™ was applied to only mild cases. The probabilistic and one-way sensitivity analyses demonstrated that incorporating Straticyte™ to the current algorithm would be cost-effective over a wide range of parameters and willingness-to-pay values. Conclusion This study demonstrates high probability that Straticyte™ and histopathology will be cost-effective, which encourages continued investment in the product. The analysis is informed by limited clinical data on Straticyte™, however as more data becomes available, more precise estimates will be generated.http://link.springer.com/article/10.1186/s13561-017-0170-6Cost-effectiveness analysisEarly health technology assessmentHistopathologyDecision- analytic modelEarly detectionPrognosis
collection DOAJ
language English
format Article
sources DOAJ
author S. Khoudigian-Sinani
G. Blackhouse
M. Levine
L. Thabane
D. O’Reilly
spellingShingle S. Khoudigian-Sinani
G. Blackhouse
M. Levine
L. Thabane
D. O’Reilly
The premarket assessment of the cost-effectiveness of a predictive technology “Straticyte™” for the early detection of oral cancer: a decision analytic model
Health Economics Review
Cost-effectiveness analysis
Early health technology assessment
Histopathology
Decision- analytic model
Early detection
Prognosis
author_facet S. Khoudigian-Sinani
G. Blackhouse
M. Levine
L. Thabane
D. O’Reilly
author_sort S. Khoudigian-Sinani
title The premarket assessment of the cost-effectiveness of a predictive technology “Straticyte™” for the early detection of oral cancer: a decision analytic model
title_short The premarket assessment of the cost-effectiveness of a predictive technology “Straticyte™” for the early detection of oral cancer: a decision analytic model
title_full The premarket assessment of the cost-effectiveness of a predictive technology “Straticyte™” for the early detection of oral cancer: a decision analytic model
title_fullStr The premarket assessment of the cost-effectiveness of a predictive technology “Straticyte™” for the early detection of oral cancer: a decision analytic model
title_full_unstemmed The premarket assessment of the cost-effectiveness of a predictive technology “Straticyte™” for the early detection of oral cancer: a decision analytic model
title_sort premarket assessment of the cost-effectiveness of a predictive technology “straticyte™” for the early detection of oral cancer: a decision analytic model
publisher BMC
series Health Economics Review
issn 2191-1991
publishDate 2017-10-01
description Abstract Introduction Approximately half of oral cancers are detected in advanced stages. The current gold standard is histopathological assessment of biopsied tissue, which is subjective and dependent on expertise. Straticyte™, a novel prognostic tool at the pre-market stage, that more accurately identifies patients at high risk for oral cancer than histopathology alone. This study conducts an early cost-effectiveness analysis (CEA) of Straticyte™ and histopathology versus histopathology alone for oral cancer diagnosis in adult patients. Methods A decision-analytic model was constructed after narrowing the scope of Straticyte™, and defining application paths. Data was gathered using the belief elicitation method, and systematic review and meta-analysis. The early CEA was conducted from private-payer and patient perspectives, capturing both direct and indirect costs over a five-year time horizon. One-way and probabilistic sensitivity analyses were conducted to investigate uncertainty. Results Compared to histopathology alone, histopathology with Straticyte™ was the dominant strategy, resulting in fewer cancer cases (31 versus 36 per 100 patients) and lower total costs per cancer case avoided (3,360 versus 3,553). This remained robust when Straticyte™ was applied to moderate and mild cases, but became slightly more expensive but still more effective than histopathology alone when Straticyte™ was applied to only mild cases. The probabilistic and one-way sensitivity analyses demonstrated that incorporating Straticyte™ to the current algorithm would be cost-effective over a wide range of parameters and willingness-to-pay values. Conclusion This study demonstrates high probability that Straticyte™ and histopathology will be cost-effective, which encourages continued investment in the product. The analysis is informed by limited clinical data on Straticyte™, however as more data becomes available, more precise estimates will be generated.
topic Cost-effectiveness analysis
Early health technology assessment
Histopathology
Decision- analytic model
Early detection
Prognosis
url http://link.springer.com/article/10.1186/s13561-017-0170-6
work_keys_str_mv AT skhoudigiansinani thepremarketassessmentofthecosteffectivenessofapredictivetechnologystraticytefortheearlydetectionoforalcanceradecisionanalyticmodel
AT gblackhouse thepremarketassessmentofthecosteffectivenessofapredictivetechnologystraticytefortheearlydetectionoforalcanceradecisionanalyticmodel
AT mlevine thepremarketassessmentofthecosteffectivenessofapredictivetechnologystraticytefortheearlydetectionoforalcanceradecisionanalyticmodel
AT lthabane thepremarketassessmentofthecosteffectivenessofapredictivetechnologystraticytefortheearlydetectionoforalcanceradecisionanalyticmodel
AT doreilly thepremarketassessmentofthecosteffectivenessofapredictivetechnologystraticytefortheearlydetectionoforalcanceradecisionanalyticmodel
AT skhoudigiansinani premarketassessmentofthecosteffectivenessofapredictivetechnologystraticytefortheearlydetectionoforalcanceradecisionanalyticmodel
AT gblackhouse premarketassessmentofthecosteffectivenessofapredictivetechnologystraticytefortheearlydetectionoforalcanceradecisionanalyticmodel
AT mlevine premarketassessmentofthecosteffectivenessofapredictivetechnologystraticytefortheearlydetectionoforalcanceradecisionanalyticmodel
AT lthabane premarketassessmentofthecosteffectivenessofapredictivetechnologystraticytefortheearlydetectionoforalcanceradecisionanalyticmodel
AT doreilly premarketassessmentofthecosteffectivenessofapredictivetechnologystraticytefortheearlydetectionoforalcanceradecisionanalyticmodel
_version_ 1725290098425069568