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Validation of models to diagnose ovarian cancer in patients managed surgically or conservatively : multicentre cohort study

Van Calster, Ben ; Valentin, Lil LU orcid ; Froyman, Wouter ; Landolfo, Chiara ; Ceusters, Jolien ; Testa, Antonia C. ; Wynants, Laure ; Sladkevicius, Povilas LU orcid ; Van Holsbeke, Caroline and Domali, Ekaterini , et al. (2020) In BMJ (Clinical research ed.) 370.
Abstract

OBJECTIVE: To evaluate the performance of diagnostic prediction models for ovarian malignancy in all patients with an ovarian mass managed surgically or conservatively. DESIGN: Multicentre cohort study. SETTING: 36 oncology referral centres (tertiary centres with a specific gynaecological oncology unit) or other types of centre. PARTICIPANTS: Consecutive adult patients presenting with an adnexal mass between January 2012 and March 2015 and managed by surgery or follow-up. MAIN OUTCOME MEASURES: Overall and centre specific discrimination, calibration, and clinical utility of six prediction models for ovarian malignancy (risk of malignancy index (RMI), logistic regression model 2 (LR2), simple rules, simple rules risk model (SRRisk),... (More)

OBJECTIVE: To evaluate the performance of diagnostic prediction models for ovarian malignancy in all patients with an ovarian mass managed surgically or conservatively. DESIGN: Multicentre cohort study. SETTING: 36 oncology referral centres (tertiary centres with a specific gynaecological oncology unit) or other types of centre. PARTICIPANTS: Consecutive adult patients presenting with an adnexal mass between January 2012 and March 2015 and managed by surgery or follow-up. MAIN OUTCOME MEASURES: Overall and centre specific discrimination, calibration, and clinical utility of six prediction models for ovarian malignancy (risk of malignancy index (RMI), logistic regression model 2 (LR2), simple rules, simple rules risk model (SRRisk), assessment of different neoplasias in the adnexa (ADNEX) with or without CA125). ADNEX allows the risk of malignancy to be subdivided into risks of a borderline, stage I primary, stage II-IV primary, or secondary metastatic malignancy. The outcome was based on histology if patients underwent surgery, or on results of clinical and ultrasound follow-up at 12 (±2) months. Multiple imputation was used when outcome based on follow-up was uncertain. RESULTS: The primary analysis included 17 centres that met strict quality criteria for surgical and follow-up data (5717 of all 8519 patients). 812 patients (14%) had a mass that was already in follow-up at study recruitment, therefore 4905 patients were included in the statistical analysis. The outcome was benign in 3441 (70%) patients and malignant in 978 (20%). Uncertain outcomes (486, 10%) were most often explained by limited follow-up information. The overall area under the receiver operating characteristic curve was highest for ADNEX with CA125 (0.94, 95% confidence interval 0.92 to 0.96), ADNEX without CA125 (0.94, 0.91 to 0.95) and SRRisk (0.94, 0.91 to 0.95), and lowest for RMI (0.89, 0.85 to 0.92). Calibration varied among centres for all models, however the ADNEX models and SRRisk were the best calibrated. Calibration of the estimated risks for the tumour subtypes was good for ADNEX irrespective of whether or not CA125 was included as a predictor. Overall clinical utility (net benefit) was highest for the ADNEX models and SRRisk, and lowest for RMI. For patients who received at least one follow-up scan (n=1958), overall area under the receiver operating characteristic curve ranged from 0.76 (95% confidence interval 0.66 to 0.84) for RMI to 0.89 (0.81 to 0.94) for ADNEX with CA125. CONCLUSIONS: Our study found the ADNEX models and SRRisk are the best models to distinguish between benign and malignant masses in all patients presenting with an adnexal mass, including those managed conservatively. TRIAL REGISTRATION: ClinicalTrials.gov NCT01698632.

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Contribution to journal
publication status
published
subject
in
BMJ (Clinical research ed.)
volume
370
article number
m2614
publisher
BMJ Publishing Group
external identifiers
  • scopus:85088885518
  • pmid:32732303
ISSN
1756-1833
DOI
10.1136/bmj.m2614
language
English
LU publication?
yes
id
41d5e198-bd41-4ba9-80e0-8cde03d4d644
date added to LUP
2021-01-04 14:15:04
date last changed
2024-04-17 22:15:29
@article{41d5e198-bd41-4ba9-80e0-8cde03d4d644,
  abstract     = {{<p>OBJECTIVE: To evaluate the performance of diagnostic prediction models for ovarian malignancy in all patients with an ovarian mass managed surgically or conservatively. DESIGN: Multicentre cohort study. SETTING: 36 oncology referral centres (tertiary centres with a specific gynaecological oncology unit) or other types of centre. PARTICIPANTS: Consecutive adult patients presenting with an adnexal mass between January 2012 and March 2015 and managed by surgery or follow-up. MAIN OUTCOME MEASURES: Overall and centre specific discrimination, calibration, and clinical utility of six prediction models for ovarian malignancy (risk of malignancy index (RMI), logistic regression model 2 (LR2), simple rules, simple rules risk model (SRRisk), assessment of different neoplasias in the adnexa (ADNEX) with or without CA125). ADNEX allows the risk of malignancy to be subdivided into risks of a borderline, stage I primary, stage II-IV primary, or secondary metastatic malignancy. The outcome was based on histology if patients underwent surgery, or on results of clinical and ultrasound follow-up at 12 (±2) months. Multiple imputation was used when outcome based on follow-up was uncertain. RESULTS: The primary analysis included 17 centres that met strict quality criteria for surgical and follow-up data (5717 of all 8519 patients). 812 patients (14%) had a mass that was already in follow-up at study recruitment, therefore 4905 patients were included in the statistical analysis. The outcome was benign in 3441 (70%) patients and malignant in 978 (20%). Uncertain outcomes (486, 10%) were most often explained by limited follow-up information. The overall area under the receiver operating characteristic curve was highest for ADNEX with CA125 (0.94, 95% confidence interval 0.92 to 0.96), ADNEX without CA125 (0.94, 0.91 to 0.95) and SRRisk (0.94, 0.91 to 0.95), and lowest for RMI (0.89, 0.85 to 0.92). Calibration varied among centres for all models, however the ADNEX models and SRRisk were the best calibrated. Calibration of the estimated risks for the tumour subtypes was good for ADNEX irrespective of whether or not CA125 was included as a predictor. Overall clinical utility (net benefit) was highest for the ADNEX models and SRRisk, and lowest for RMI. For patients who received at least one follow-up scan (n=1958), overall area under the receiver operating characteristic curve ranged from 0.76 (95% confidence interval 0.66 to 0.84) for RMI to 0.89 (0.81 to 0.94) for ADNEX with CA125. CONCLUSIONS: Our study found the ADNEX models and SRRisk are the best models to distinguish between benign and malignant masses in all patients presenting with an adnexal mass, including those managed conservatively. TRIAL REGISTRATION: ClinicalTrials.gov NCT01698632.</p>}},
  author       = {{Van Calster, Ben and Valentin, Lil and Froyman, Wouter and Landolfo, Chiara and Ceusters, Jolien and Testa, Antonia C. and Wynants, Laure and Sladkevicius, Povilas and Van Holsbeke, Caroline and Domali, Ekaterini and Fruscio, Robert and Epstein, Elisabeth and Franchi, Dorella and Kudla, Marek J. and Chiappa, Valentina and Alcazar, Juan L. and Leone, Francesco P.G. and Buonomo, Francesca and Coccia, Maria Elisabetta and Guerriero, Stefano and Deo, Nandita and Jokubkiene, Ligita and Savelli, Luca and Fischerová, Daniela and Czekierdowski, Artur and Kaijser, Jeroen and Coosemans, An and Scambia, Giovanni and Vergote, Ignace and Bourne, Tom and Timmerman, Dirk}},
  issn         = {{1756-1833}},
  language     = {{eng}},
  publisher    = {{BMJ Publishing Group}},
  series       = {{BMJ (Clinical research ed.)}},
  title        = {{Validation of models to diagnose ovarian cancer in patients managed surgically or conservatively : multicentre cohort study}},
  url          = {{http://dx.doi.org/10.1136/bmj.m2614}},
  doi          = {{10.1136/bmj.m2614}},
  volume       = {{370}},
  year         = {{2020}},
}