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...
Main Authors: | , , , , |
---|---|
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 |