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Economic evaluation of an expert examiner and different ultrasound models in the diagnosis of ovarian cancer
The Risk of Malignancy Index (RMI) is commonly used to diagnose adnexal masses. The aim of the present study was to determine the cost-effectiveness of the RMI compared with subjective assessment (SA) by an expert and the following novel ultrasound models: -Simple rules (SR) added by SA (SR + SA);-S...
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| Published in: | European journal of cancer (1990) 2018-09, Vol.100, p.55-64 |
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| container_title | European journal of cancer (1990) |
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| creator | Meys, Evelyne M.J. Jeelof, Lara S. Ramaekers, Bram L.T. Dirksen, Carmen D. Kooreman, Loes F.S. Slangen, Brigitte F.M. Kruitwagen, Roy F.P.M. Van Gorp, Toon |
| description | The Risk of Malignancy Index (RMI) is commonly used to diagnose adnexal masses. The aim of the present study was to determine the cost-effectiveness of the RMI compared with subjective assessment (SA) by an expert and the following novel ultrasound models:
-Simple rules (SR) added by SA (SR + SA);-SR with inconclusive results diagnosed as malignant (SR + Mal);-Logistic Regression model 2 (LR2); and-Assessment of Different NEoplasias in the adneXa (ADNEX) model.
Cost-effectiveness and budget impact analyses were performed from a societal perspective. A decision tree was constructed, and short-term costs and effects were examined in women with adnexal masses. Sensitivity, specificity and the costs of diagnostic strategies were incorporated. Incremental cost-effectiveness ratios were expressed as costs/additional percentage of correctly diagnosed patients. Probabilistic and deterministic sensitivity analyses were performed.
Effectiveness was highest for SA (90.7% [95% confidence interval = 77.3–100]), with a cost saving of 5.0% (−€398 per patient [−€1403 to 549]) compared with the RMI. The costs of SR + SA were the lowest (€7180 [6072–8436]), resulting in a cost saving of 9.0% (−€709 per patient [−€1628 to 236]) compared with the RMI, with an effectiveness of 89.6% (75.8–100). SR + SA showed the highest probability of being the most cost-effective when willingness-to-pay was |
| doi_str_mv | 10.1016/j.ejca.2018.05.003 |
| format | article |
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-Simple rules (SR) added by SA (SR + SA);-SR with inconclusive results diagnosed as malignant (SR + Mal);-Logistic Regression model 2 (LR2); and-Assessment of Different NEoplasias in the adneXa (ADNEX) model.
Cost-effectiveness and budget impact analyses were performed from a societal perspective. A decision tree was constructed, and short-term costs and effects were examined in women with adnexal masses. Sensitivity, specificity and the costs of diagnostic strategies were incorporated. Incremental cost-effectiveness ratios were expressed as costs/additional percentage of correctly diagnosed patients. Probabilistic and deterministic sensitivity analyses were performed.
Effectiveness was highest for SA (90.7% [95% confidence interval = 77.3–100]), with a cost saving of 5.0% (−€398 per patient [−€1403 to 549]) compared with the RMI. The costs of SR + SA were the lowest (€7180 [6072–8436]), resulting in a cost saving of 9.0% (−€709 per patient [−€1628 to 236]) compared with the RMI, with an effectiveness of 89.6% (75.8–100). SR + SA showed the highest probability of being the most cost-effective when willingness-to-pay was <€350 per additional percentage of correctly diagnosed patients. The RMI had low cost-effectiveness probabilities (<3%) and was inferior to SA, SR + SA and LR2. Budget impact in the Netherlands compared with that of the RMI varied between a cost saving of €4.67 million for SR + SA and additional costs of €3.83 million when implementing ADNEX (cut-off: 10%). The results were robust when tested in sensitivity analyses.
Although SA is the best strategy in terms of diagnostic accuracy, SR + SA might be preferred from a cost-effectiveness perspective.
•This is the first cost-effectiveness analysis on subjective assessment (SA) to classify adnexal masses.•Cost-effectiveness of risk of malignancy index (RMI) was compared with SA and novel ultrasound models.•Effectiveness was highest for SA, with a cost saving of 5.0% compared to RMI.•Costs of simple rules added with SA for inconclusive results (SR [simple rules] + SA) were lowest.•Therefore, SR + SA might be preferred from a cost-effectiveness perspective.</description><identifier>ISSN: 0959-8049</identifier><identifier>EISSN: 1879-0852</identifier><identifier>DOI: 10.1016/j.ejca.2018.05.003</identifier><identifier>PMID: 29957561</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>Absenteeism ; ADNEX model ; Budget impact analysis ; Budgets ; Confidence intervals ; Construction costs ; Cost analysis ; Cost engineering ; Cost-Benefit Analysis ; Cost-effectiveness analysis ; Decision analysis ; Decision Support Techniques ; Decision Trees ; Diagnosis ; Diagnostic Errors - economics ; Diagnostic systems ; Economic models ; Female ; Health Care Costs ; Health Expenditures ; Health risks ; Humans ; Impact analysis ; LR2 model ; Malignancy ; Medical diagnosis ; Medical treatment ; Models, Economic ; Netherlands - epidemiology ; Ovarian cancer ; Ovarian Neoplasms - diagnostic imaging ; Ovarian Neoplasms - economics ; Ovarian Neoplasms - epidemiology ; Ovarian Neoplasms - pathology ; Patients ; Predictive Value of Tests ; Prevalence ; Regression analysis ; Regression models ; Reproducibility of Results ; RMI ; Sensitivity ; Sensitivity analysis ; Sick Leave - economics ; Simple ultrasound-based rules ; Statistical analysis ; Studies ; Subjective assessment ; Ultrasonic imaging ; Ultrasonography - economics ; Ultrasound</subject><ispartof>European journal of cancer (1990), 2018-09, Vol.100, p.55-64</ispartof><rights>2018 Elsevier Ltd</rights><rights>Copyright © 2018 Elsevier Ltd. All rights reserved.</rights><rights>Copyright Elsevier Science Ltd. Sep 2018</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c428t-72e614be3c3b513ebbeb3181b79388e7f1db4835b84e5e9c6b050c32e2df20f43</citedby><cites>FETCH-LOGICAL-c428t-72e614be3c3b513ebbeb3181b79388e7f1db4835b84e5e9c6b050c32e2df20f43</cites><orcidid>0000-0001-6685-3717</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29957561$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Meys, Evelyne M.J.</creatorcontrib><creatorcontrib>Jeelof, Lara S.</creatorcontrib><creatorcontrib>Ramaekers, Bram L.T.</creatorcontrib><creatorcontrib>Dirksen, Carmen D.</creatorcontrib><creatorcontrib>Kooreman, Loes F.S.</creatorcontrib><creatorcontrib>Slangen, Brigitte F.M.</creatorcontrib><creatorcontrib>Kruitwagen, Roy F.P.M.</creatorcontrib><creatorcontrib>Van Gorp, Toon</creatorcontrib><title>Economic evaluation of an expert examiner and different ultrasound models in the diagnosis of ovarian cancer</title><title>European journal of cancer (1990)</title><addtitle>Eur J Cancer</addtitle><description>The Risk of Malignancy Index (RMI) is commonly used to diagnose adnexal masses. The aim of the present study was to determine the cost-effectiveness of the RMI compared with subjective assessment (SA) by an expert and the following novel ultrasound models:
-Simple rules (SR) added by SA (SR + SA);-SR with inconclusive results diagnosed as malignant (SR + Mal);-Logistic Regression model 2 (LR2); and-Assessment of Different NEoplasias in the adneXa (ADNEX) model.
Cost-effectiveness and budget impact analyses were performed from a societal perspective. A decision tree was constructed, and short-term costs and effects were examined in women with adnexal masses. Sensitivity, specificity and the costs of diagnostic strategies were incorporated. Incremental cost-effectiveness ratios were expressed as costs/additional percentage of correctly diagnosed patients. Probabilistic and deterministic sensitivity analyses were performed.
Effectiveness was highest for SA (90.7% [95% confidence interval = 77.3–100]), with a cost saving of 5.0% (−€398 per patient [−€1403 to 549]) compared with the RMI. The costs of SR + SA were the lowest (€7180 [6072–8436]), resulting in a cost saving of 9.0% (−€709 per patient [−€1628 to 236]) compared with the RMI, with an effectiveness of 89.6% (75.8–100). SR + SA showed the highest probability of being the most cost-effective when willingness-to-pay was <€350 per additional percentage of correctly diagnosed patients. The RMI had low cost-effectiveness probabilities (<3%) and was inferior to SA, SR + SA and LR2. Budget impact in the Netherlands compared with that of the RMI varied between a cost saving of €4.67 million for SR + SA and additional costs of €3.83 million when implementing ADNEX (cut-off: 10%). The results were robust when tested in sensitivity analyses.
Although SA is the best strategy in terms of diagnostic accuracy, SR + SA might be preferred from a cost-effectiveness perspective.
•This is the first cost-effectiveness analysis on subjective assessment (SA) to classify adnexal masses.•Cost-effectiveness of risk of malignancy index (RMI) was compared with SA and novel ultrasound models.•Effectiveness was highest for SA, with a cost saving of 5.0% compared to RMI.•Costs of simple rules added with SA for inconclusive results (SR [simple rules] + SA) were lowest.•Therefore, SR + SA might be preferred from a cost-effectiveness perspective.</description><subject>Absenteeism</subject><subject>ADNEX model</subject><subject>Budget impact analysis</subject><subject>Budgets</subject><subject>Confidence intervals</subject><subject>Construction costs</subject><subject>Cost analysis</subject><subject>Cost engineering</subject><subject>Cost-Benefit Analysis</subject><subject>Cost-effectiveness analysis</subject><subject>Decision analysis</subject><subject>Decision Support Techniques</subject><subject>Decision Trees</subject><subject>Diagnosis</subject><subject>Diagnostic Errors - economics</subject><subject>Diagnostic systems</subject><subject>Economic models</subject><subject>Female</subject><subject>Health Care Costs</subject><subject>Health Expenditures</subject><subject>Health risks</subject><subject>Humans</subject><subject>Impact analysis</subject><subject>LR2 model</subject><subject>Malignancy</subject><subject>Medical diagnosis</subject><subject>Medical treatment</subject><subject>Models, Economic</subject><subject>Netherlands - epidemiology</subject><subject>Ovarian cancer</subject><subject>Ovarian Neoplasms - diagnostic imaging</subject><subject>Ovarian Neoplasms - economics</subject><subject>Ovarian Neoplasms - epidemiology</subject><subject>Ovarian Neoplasms - pathology</subject><subject>Patients</subject><subject>Predictive Value of Tests</subject><subject>Prevalence</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Reproducibility of Results</subject><subject>RMI</subject><subject>Sensitivity</subject><subject>Sensitivity analysis</subject><subject>Sick Leave - economics</subject><subject>Simple ultrasound-based rules</subject><subject>Statistical analysis</subject><subject>Studies</subject><subject>Subjective assessment</subject><subject>Ultrasonic imaging</subject><subject>Ultrasonography - economics</subject><subject>Ultrasound</subject><issn>0959-8049</issn><issn>1879-0852</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNp9kU2L1TAUhoM4ONfRP-BCCm5m03qSNG0CbmQYP2DAzbgOSXqqKW1yTdqL8-8n5Y4uXLg6cHjOw-F9CXlDoaFAu_dTg5MzDQMqGxANAH9GDlT2qgYp2HNyACVULaFVl-RlzhMA9LKFF-SSKSV60dEDmW9dDHHxrsKTmTez-hiqOFYmVPj7iGktwyw-YCqroRr8OGLCsFbbvCaT41aWSxxwzpUP1foTC2J-hJh93jXxZJIvLmeCw_SKXIxmzvj6aV6R759u72--1HffPn-9-XhXu5bJte4ZdrS1yB23gnK0Fi2nktpecSmxH-lgW8mFlS0KVK6zIMBxhmwYGYwtvyLXZ-8xxV8b5lUvPjucZxMwblkz6JjkoOSOvvsHneKWQvlOM0oZA9G1rFDsTLkUc0446mPyi0kPmoLeu9CT3rvQexcahC5dlKO3T-rNLjj8PfkTfgE-nIGSHp48Jp2dxxLU4BO6VQ_R_8__CMm-myA</recordid><startdate>201809</startdate><enddate>201809</enddate><creator>Meys, Evelyne M.J.</creator><creator>Jeelof, Lara S.</creator><creator>Ramaekers, Bram L.T.</creator><creator>Dirksen, Carmen D.</creator><creator>Kooreman, Loes F.S.</creator><creator>Slangen, Brigitte F.M.</creator><creator>Kruitwagen, Roy F.P.M.</creator><creator>Van Gorp, Toon</creator><general>Elsevier Ltd</general><general>Elsevier Science Ltd</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TO</scope><scope>7U7</scope><scope>C1K</scope><scope>H94</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-6685-3717</orcidid></search><sort><creationdate>201809</creationdate><title>Economic evaluation of an expert examiner and different ultrasound models in the diagnosis of ovarian cancer</title><author>Meys, Evelyne M.J. ; Jeelof, Lara S. ; Ramaekers, Bram L.T. ; Dirksen, Carmen D. ; Kooreman, Loes F.S. ; Slangen, Brigitte F.M. ; Kruitwagen, Roy F.P.M. ; Van Gorp, Toon</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c428t-72e614be3c3b513ebbeb3181b79388e7f1db4835b84e5e9c6b050c32e2df20f43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Absenteeism</topic><topic>ADNEX model</topic><topic>Budget impact analysis</topic><topic>Budgets</topic><topic>Confidence intervals</topic><topic>Construction costs</topic><topic>Cost analysis</topic><topic>Cost engineering</topic><topic>Cost-Benefit Analysis</topic><topic>Cost-effectiveness analysis</topic><topic>Decision analysis</topic><topic>Decision Support Techniques</topic><topic>Decision Trees</topic><topic>Diagnosis</topic><topic>Diagnostic Errors - economics</topic><topic>Diagnostic systems</topic><topic>Economic models</topic><topic>Female</topic><topic>Health Care Costs</topic><topic>Health Expenditures</topic><topic>Health risks</topic><topic>Humans</topic><topic>Impact analysis</topic><topic>LR2 model</topic><topic>Malignancy</topic><topic>Medical diagnosis</topic><topic>Medical treatment</topic><topic>Models, Economic</topic><topic>Netherlands - epidemiology</topic><topic>Ovarian cancer</topic><topic>Ovarian Neoplasms - diagnostic imaging</topic><topic>Ovarian Neoplasms - economics</topic><topic>Ovarian Neoplasms - epidemiology</topic><topic>Ovarian Neoplasms - pathology</topic><topic>Patients</topic><topic>Predictive Value of Tests</topic><topic>Prevalence</topic><topic>Regression analysis</topic><topic>Regression models</topic><topic>Reproducibility of Results</topic><topic>RMI</topic><topic>Sensitivity</topic><topic>Sensitivity analysis</topic><topic>Sick Leave - economics</topic><topic>Simple ultrasound-based rules</topic><topic>Statistical analysis</topic><topic>Studies</topic><topic>Subjective assessment</topic><topic>Ultrasonic imaging</topic><topic>Ultrasonography - economics</topic><topic>Ultrasound</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Meys, Evelyne M.J.</creatorcontrib><creatorcontrib>Jeelof, Lara S.</creatorcontrib><creatorcontrib>Ramaekers, Bram L.T.</creatorcontrib><creatorcontrib>Dirksen, Carmen D.</creatorcontrib><creatorcontrib>Kooreman, Loes F.S.</creatorcontrib><creatorcontrib>Slangen, Brigitte F.M.</creatorcontrib><creatorcontrib>Kruitwagen, Roy F.P.M.</creatorcontrib><creatorcontrib>Van Gorp, Toon</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Premium</collection><collection>MEDLINE - Academic</collection><jtitle>European journal of cancer (1990)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Meys, Evelyne M.J.</au><au>Jeelof, Lara S.</au><au>Ramaekers, Bram L.T.</au><au>Dirksen, Carmen D.</au><au>Kooreman, Loes F.S.</au><au>Slangen, Brigitte F.M.</au><au>Kruitwagen, Roy F.P.M.</au><au>Van Gorp, Toon</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Economic evaluation of an expert examiner and different ultrasound models in the diagnosis of ovarian cancer</atitle><jtitle>European journal of cancer (1990)</jtitle><addtitle>Eur J Cancer</addtitle><date>2018-09</date><risdate>2018</risdate><volume>100</volume><spage>55</spage><epage>64</epage><pages>55-64</pages><issn>0959-8049</issn><eissn>1879-0852</eissn><abstract>The Risk of Malignancy Index (RMI) is commonly used to diagnose adnexal masses. The aim of the present study was to determine the cost-effectiveness of the RMI compared with subjective assessment (SA) by an expert and the following novel ultrasound models:
-Simple rules (SR) added by SA (SR + SA);-SR with inconclusive results diagnosed as malignant (SR + Mal);-Logistic Regression model 2 (LR2); and-Assessment of Different NEoplasias in the adneXa (ADNEX) model.
Cost-effectiveness and budget impact analyses were performed from a societal perspective. A decision tree was constructed, and short-term costs and effects were examined in women with adnexal masses. Sensitivity, specificity and the costs of diagnostic strategies were incorporated. Incremental cost-effectiveness ratios were expressed as costs/additional percentage of correctly diagnosed patients. Probabilistic and deterministic sensitivity analyses were performed.
Effectiveness was highest for SA (90.7% [95% confidence interval = 77.3–100]), with a cost saving of 5.0% (−€398 per patient [−€1403 to 549]) compared with the RMI. The costs of SR + SA were the lowest (€7180 [6072–8436]), resulting in a cost saving of 9.0% (−€709 per patient [−€1628 to 236]) compared with the RMI, with an effectiveness of 89.6% (75.8–100). SR + SA showed the highest probability of being the most cost-effective when willingness-to-pay was <€350 per additional percentage of correctly diagnosed patients. The RMI had low cost-effectiveness probabilities (<3%) and was inferior to SA, SR + SA and LR2. Budget impact in the Netherlands compared with that of the RMI varied between a cost saving of €4.67 million for SR + SA and additional costs of €3.83 million when implementing ADNEX (cut-off: 10%). The results were robust when tested in sensitivity analyses.
Although SA is the best strategy in terms of diagnostic accuracy, SR + SA might be preferred from a cost-effectiveness perspective.
•This is the first cost-effectiveness analysis on subjective assessment (SA) to classify adnexal masses.•Cost-effectiveness of risk of malignancy index (RMI) was compared with SA and novel ultrasound models.•Effectiveness was highest for SA, with a cost saving of 5.0% compared to RMI.•Costs of simple rules added with SA for inconclusive results (SR [simple rules] + SA) were lowest.•Therefore, SR + SA might be preferred from a cost-effectiveness perspective.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>29957561</pmid><doi>10.1016/j.ejca.2018.05.003</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0001-6685-3717</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | European journal of cancer (1990), 2018-09, Vol.100, p.55-64 |
| issn | 0959-8049 1879-0852 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_2062830984 |
| source | ScienceDirect Freedom Collection 2022-2024 |
| subjects | Absenteeism ADNEX model Budget impact analysis Budgets Confidence intervals Construction costs Cost analysis Cost engineering Cost-Benefit Analysis Cost-effectiveness analysis Decision analysis Decision Support Techniques Decision Trees Diagnosis Diagnostic Errors - economics Diagnostic systems Economic models Female Health Care Costs Health Expenditures Health risks Humans Impact analysis LR2 model Malignancy Medical diagnosis Medical treatment Models, Economic Netherlands - epidemiology Ovarian cancer Ovarian Neoplasms - diagnostic imaging Ovarian Neoplasms - economics Ovarian Neoplasms - epidemiology Ovarian Neoplasms - pathology Patients Predictive Value of Tests Prevalence Regression analysis Regression models Reproducibility of Results RMI Sensitivity Sensitivity analysis Sick Leave - economics Simple ultrasound-based rules Statistical analysis Studies Subjective assessment Ultrasonic imaging Ultrasonography - economics Ultrasound |
| title | Economic evaluation of an expert examiner and different ultrasound models in the diagnosis of ovarian cancer |
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