BACKGROUND: Ovarian cancer (OC) is a diagnostic challenge, with the majority diagnosed at late stages. Existing systematic reviews of diagnostic models either use inappropriate meta-analytic methods or do not conduct statistical comparisons of models or stratify test performance by menopausal status. METHODS: We searched CENTRAL, MEDLINE, EMBASE, CINAHL, CDSR, DARE, Health Technology Assessment Database and SCI Science Citation Index, trials registers, conference proceedings from 1991 to June 2019. Cochrane collaboration review methods included QUADAS-2 quality assessment and meta-analysis using hierarchical modelling. RMI, ROMA or ADNEX at any test positivity threshold were investigated. Histology or clinical follow-up was the reference st...
Introduction: Ovarian cancer (OC) diagnosis remains a clinical challenge due to lack of early sympto...
OBJECTIVETo evaluate the performance of diagnostic prediction models for ovarian malignancy in all p...
Objectives To evaluate the utility of pre-operative diagnostic models for ovarian cancer based on ul...
BACKGROUND: Ovarian cancer (OC) is a diagnostic challenge, with the majority diagnosed at late stage...
BACKGROUND: Ovarian cancer (OC) is a diagnostic challenge, with the majority diagnosed at late stage...
Background: Ovarian cancer (OC) has the highest case fatality rate of all gynaecological cancers. Di...
BACKGROUND: Ovarian cancer (OC) has the highest case fatality rate of all gynaecological cancers. Di...
Objective To evaluate the performance of diagnostic prediction models for ovarian malignancy in all ...
The International Ovarian Tumour Analysis (IOTA) group have developed the ADNEX (The Assessment of D...
© The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 Internationa...
To evaluate the utility of pre-operative diagnostic models for ovarian cancer based on ultrasound an...
Background: Ovarian cancer possesses a challenge to screening tests due to its anatomical location, ...
Objective The International ovarian tumor analysis (IOTA)-Assessment of Different NEoplasias in the ...
Background: To compare different ultrasound-based international ovarian tumour analysis (IOTA) strat...
Whilst patients with ovarian cancer clearly benefit from centralised, comprehensive care in dedicate...
Introduction: Ovarian cancer (OC) diagnosis remains a clinical challenge due to lack of early sympto...
OBJECTIVETo evaluate the performance of diagnostic prediction models for ovarian malignancy in all p...
Objectives To evaluate the utility of pre-operative diagnostic models for ovarian cancer based on ul...
BACKGROUND: Ovarian cancer (OC) is a diagnostic challenge, with the majority diagnosed at late stage...
BACKGROUND: Ovarian cancer (OC) is a diagnostic challenge, with the majority diagnosed at late stage...
Background: Ovarian cancer (OC) has the highest case fatality rate of all gynaecological cancers. Di...
BACKGROUND: Ovarian cancer (OC) has the highest case fatality rate of all gynaecological cancers. Di...
Objective To evaluate the performance of diagnostic prediction models for ovarian malignancy in all ...
The International Ovarian Tumour Analysis (IOTA) group have developed the ADNEX (The Assessment of D...
© The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 Internationa...
To evaluate the utility of pre-operative diagnostic models for ovarian cancer based on ultrasound an...
Background: Ovarian cancer possesses a challenge to screening tests due to its anatomical location, ...
Objective The International ovarian tumor analysis (IOTA)-Assessment of Different NEoplasias in the ...
Background: To compare different ultrasound-based international ovarian tumour analysis (IOTA) strat...
Whilst patients with ovarian cancer clearly benefit from centralised, comprehensive care in dedicate...
Introduction: Ovarian cancer (OC) diagnosis remains a clinical challenge due to lack of early sympto...
OBJECTIVETo evaluate the performance of diagnostic prediction models for ovarian malignancy in all p...
Objectives To evaluate the utility of pre-operative diagnostic models for ovarian cancer based on ul...