Clinical utility of risk models to refer patients with adnexal masses to specialized oncology care: multicenter external validation using decision curve analysis.
<h4>Objectives</h4> <p>To evaluate the utility of pre-operative diagnostic models for ovarian cancer based on ultrasound and/or biomarkers for referring patients to specialized oncology care. The investigated models were RMI, ROMA, and three models from the International Ovarian T...
| Main Authors: | , , , , , , , , , , , , , , , , |
|---|---|
| Format: | Journal article |
| Language: | English |
| Published: |
American Association for Cancer Research
2017
|
| _version_ | 1826290021266620416 |
|---|---|
| author | Wynants, L Timmerman, D Verbakel, J Testa, A Savelli, L Fischerova, D Franchi, D Van Holsbeke, C Epstein, E Froyman, W Guerriero, S Rossi, A Fruscio, R Leone, F Bourne, T Valentin, L Van Calster, B |
| author_facet | Wynants, L Timmerman, D Verbakel, J Testa, A Savelli, L Fischerova, D Franchi, D Van Holsbeke, C Epstein, E Froyman, W Guerriero, S Rossi, A Fruscio, R Leone, F Bourne, T Valentin, L Van Calster, B |
| author_sort | Wynants, L |
| collection | OXFORD |
| description | <h4>Objectives</h4> <p>To evaluate the utility of pre-operative diagnostic models for ovarian cancer based on ultrasound and/or biomarkers for referring patients to specialized oncology care. The investigated models were RMI, ROMA, and three models from the International Ovarian Tumor Analysis (IOTA) group (LR2, ADNEX, and the Simple Rules risk score, SRRisks).</p> <h4>Design</h4> <p>A secondary analysis of prospectively collected data from two cross-sectional cohort studies performed to externally validate diagnostic models.</p> <h4>Participants</h4> <p>A total of 2763 patients (2403 in dataset 1 and 360 in dataset 2) from 18 centers (11 oncology centers and 7 non-oncology hospitals) in 6 countries.</p> <h4>Main Outcome Measure</h4> <p>Excised tissue was histologically classified as benign or malignant. The clinical utility of the pre-operative diagnostic models was assessed with Net Benefit (NB) at a range of risk thresholds (5% to 50% risk of malignancy) to refer patients to specialized oncology care. We visualized results with decision curves and generated bootstrap confidence intervals.</p> <h4>Results</h4> <p>The prevalence of malignancy was 41% in dataset 1 and 40% in dataset 2. For thresholds up to 10%-15%, RMI and ROMA had a lower NB than referring all patients. SRRisks and ADNEX demonstrated the highest NB. At a threshold of 20%, the NBs of ADNEX, SRrisks and RMI were 0.348, 0.350, and 0.270, respectively. Results by menopausal status and type of center (oncology versus non-oncology) were similar.</p> <h4>Conclusions</h4> <p>All tested IOTA methods, especially ADNEX and SRRisks, are clinically more useful than RMI and ROMA to select patients with adnexal masses for specialized oncology care.</p> |
| first_indexed | 2024-03-07T02:37:49Z |
| format | Journal article |
| id | oxford-uuid:a96029c6-d3d7-4494-88b6-98bbda426898 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T02:37:49Z |
| publishDate | 2017 |
| publisher | American Association for Cancer Research |
| record_format | dspace |
| spelling | oxford-uuid:a96029c6-d3d7-4494-88b6-98bbda4268982022-03-27T03:08:09ZClinical utility of risk models to refer patients with adnexal masses to specialized oncology care: multicenter external validation using decision curve analysis.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:a96029c6-d3d7-4494-88b6-98bbda426898EnglishSymplectic Elements at OxfordAmerican Association for Cancer Research2017Wynants, LTimmerman, DVerbakel, JTesta, ASavelli, LFischerova, DFranchi, DVan Holsbeke, CEpstein, EFroyman, WGuerriero, SRossi, AFruscio, RLeone, FBourne, TValentin, LVan Calster, B <h4>Objectives</h4> <p>To evaluate the utility of pre-operative diagnostic models for ovarian cancer based on ultrasound and/or biomarkers for referring patients to specialized oncology care. The investigated models were RMI, ROMA, and three models from the International Ovarian Tumor Analysis (IOTA) group (LR2, ADNEX, and the Simple Rules risk score, SRRisks).</p> <h4>Design</h4> <p>A secondary analysis of prospectively collected data from two cross-sectional cohort studies performed to externally validate diagnostic models.</p> <h4>Participants</h4> <p>A total of 2763 patients (2403 in dataset 1 and 360 in dataset 2) from 18 centers (11 oncology centers and 7 non-oncology hospitals) in 6 countries.</p> <h4>Main Outcome Measure</h4> <p>Excised tissue was histologically classified as benign or malignant. The clinical utility of the pre-operative diagnostic models was assessed with Net Benefit (NB) at a range of risk thresholds (5% to 50% risk of malignancy) to refer patients to specialized oncology care. We visualized results with decision curves and generated bootstrap confidence intervals.</p> <h4>Results</h4> <p>The prevalence of malignancy was 41% in dataset 1 and 40% in dataset 2. For thresholds up to 10%-15%, RMI and ROMA had a lower NB than referring all patients. SRRisks and ADNEX demonstrated the highest NB. At a threshold of 20%, the NBs of ADNEX, SRrisks and RMI were 0.348, 0.350, and 0.270, respectively. Results by menopausal status and type of center (oncology versus non-oncology) were similar.</p> <h4>Conclusions</h4> <p>All tested IOTA methods, especially ADNEX and SRRisks, are clinically more useful than RMI and ROMA to select patients with adnexal masses for specialized oncology care.</p> |
| spellingShingle | Wynants, L Timmerman, D Verbakel, J Testa, A Savelli, L Fischerova, D Franchi, D Van Holsbeke, C Epstein, E Froyman, W Guerriero, S Rossi, A Fruscio, R Leone, F Bourne, T Valentin, L Van Calster, B Clinical utility of risk models to refer patients with adnexal masses to specialized oncology care: multicenter external validation using decision curve analysis. |
| title | Clinical utility of risk models to refer patients with adnexal masses to specialized oncology care: multicenter external validation using decision curve analysis. |
| title_full | Clinical utility of risk models to refer patients with adnexal masses to specialized oncology care: multicenter external validation using decision curve analysis. |
| title_fullStr | Clinical utility of risk models to refer patients with adnexal masses to specialized oncology care: multicenter external validation using decision curve analysis. |
| title_full_unstemmed | Clinical utility of risk models to refer patients with adnexal masses to specialized oncology care: multicenter external validation using decision curve analysis. |
| title_short | Clinical utility of risk models to refer patients with adnexal masses to specialized oncology care: multicenter external validation using decision curve analysis. |
| title_sort | clinical utility of risk models to refer patients with adnexal masses to specialized oncology care multicenter external validation using decision curve analysis |
| work_keys_str_mv | AT wynantsl clinicalutilityofriskmodelstoreferpatientswithadnexalmassestospecializedoncologycaremulticenterexternalvalidationusingdecisioncurveanalysis AT timmermand clinicalutilityofriskmodelstoreferpatientswithadnexalmassestospecializedoncologycaremulticenterexternalvalidationusingdecisioncurveanalysis AT verbakelj clinicalutilityofriskmodelstoreferpatientswithadnexalmassestospecializedoncologycaremulticenterexternalvalidationusingdecisioncurveanalysis AT testaa clinicalutilityofriskmodelstoreferpatientswithadnexalmassestospecializedoncologycaremulticenterexternalvalidationusingdecisioncurveanalysis AT savellil clinicalutilityofriskmodelstoreferpatientswithadnexalmassestospecializedoncologycaremulticenterexternalvalidationusingdecisioncurveanalysis AT fischerovad clinicalutilityofriskmodelstoreferpatientswithadnexalmassestospecializedoncologycaremulticenterexternalvalidationusingdecisioncurveanalysis AT franchid clinicalutilityofriskmodelstoreferpatientswithadnexalmassestospecializedoncologycaremulticenterexternalvalidationusingdecisioncurveanalysis AT vanholsbekec clinicalutilityofriskmodelstoreferpatientswithadnexalmassestospecializedoncologycaremulticenterexternalvalidationusingdecisioncurveanalysis AT epsteine clinicalutilityofriskmodelstoreferpatientswithadnexalmassestospecializedoncologycaremulticenterexternalvalidationusingdecisioncurveanalysis AT froymanw clinicalutilityofriskmodelstoreferpatientswithadnexalmassestospecializedoncologycaremulticenterexternalvalidationusingdecisioncurveanalysis AT guerrieros clinicalutilityofriskmodelstoreferpatientswithadnexalmassestospecializedoncologycaremulticenterexternalvalidationusingdecisioncurveanalysis AT rossia clinicalutilityofriskmodelstoreferpatientswithadnexalmassestospecializedoncologycaremulticenterexternalvalidationusingdecisioncurveanalysis AT fruscior clinicalutilityofriskmodelstoreferpatientswithadnexalmassestospecializedoncologycaremulticenterexternalvalidationusingdecisioncurveanalysis AT leonef clinicalutilityofriskmodelstoreferpatientswithadnexalmassestospecializedoncologycaremulticenterexternalvalidationusingdecisioncurveanalysis AT bournet clinicalutilityofriskmodelstoreferpatientswithadnexalmassestospecializedoncologycaremulticenterexternalvalidationusingdecisioncurveanalysis AT valentinl clinicalutilityofriskmodelstoreferpatientswithadnexalmassestospecializedoncologycaremulticenterexternalvalidationusingdecisioncurveanalysis AT vancalsterb clinicalutilityofriskmodelstoreferpatientswithadnexalmassestospecializedoncologycaremulticenterexternalvalidationusingdecisioncurveanalysis |