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Towards an evidence-based approach for diagnosis and management of adnexal masses: findings of the International Ovarian Tumour Analysis (IOTA) studies.

Kaijser J - Facts Views Vis Obgyn (2015)

Bottom Line: They also offer more accurate triage compared to the existing Risk of Malignancy Index (RMI).The development of the IOTA ADNEX model represents an important step forward towards more individualised patient care in this area.The IOTA study has made significant progress in relation to the classification of adnexal masses, however what is now needed is to see if these or new diagnostic tools can assist clinicians to select patients with adnexal masses that are suitable for expectant management, and that will work in all health care settings (i.e. primary vs secondary vs tertiary care).

View Article: PubMed Central - PubMed

Affiliation: KU Leuven, Department of Development and Regeneration, Leuven, Belgium. ; Department of Obstetrics and Gynaecology, University Hospitals KU Leuven, Leuven, Belgium.

ABSTRACT
Whilst the outcomes for patients with ovarian cancer clearly benefit from centralised, comprehensive care in dedicated cancer centres, unfortunately the majority of patients still do not receive appropriate specialist treatment. Any improvement in the accuracy of current triaging and referral pathways whether using new imaging tests or biomarkers would therefore be of value in order to optimise the appropriate selection of patients for such care. An analysis of current evidence shows that such tests are now available, but still await recognition, acceptance and widespread adoption. It is therefore to be hoped that present guidance relating to the classification of ovarian masses will soon become more "evidence-based". These promising tests include the International Ovarian Tumour Analysis (IOTA) LR2 model and ultrasound-based Simple Rules (SR). Based on a comprehensive recent meta-analysis both currently offer the optimal "evidence-based" approach to discriminating between cancer and benign conditions in women with adnexal tumours needing surgery. LR2 and SR are reliable tests having been shown to maintain a high sensitivity for cancer after independent external and temporal validation by the IOTA group in the hands of examiners with various levels of ultrasound expertise. They also offer more accurate triage compared to the existing Risk of Malignancy Index (RMI). The development of the IOTA ADNEX model represents an important step forward towards more individualised patient care in this area. ADNEX is a novel test that enables the more specific subtyping of adnexal cancers (i.e. borderline, stage 1 invasive, stage II-IV invasive, and secondary metastatic malignant tumours) and shares similar levels of accuracy to IOTA LR2 and SR for basic discrimination between cancer and benign disease. The IOTA study has made significant progress in relation to the classification of adnexal masses, however what is now needed is to see if these or new diagnostic tools can assist clinicians to select patients with adnexal masses that are suitable for expectant management, and that will work in all health care settings (i.e. primary vs secondary vs tertiary care). These important themes will likely control the future agenda of the IOTA project.

No MeSH data available.


Related in: MedlinePlus

Receiver operating characteristic (ROC) curves for the logistic regression model 2 (LR2), Assessment of Different NEoplasias in the AdneXa (ADNEX) model and Risk of Malignancy Index (RMI) with ROC points for the Simple Rules superimposed. The results were obtained using pooled data (n = 2403) from IOTA phase 3.
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Figure 3: Receiver operating characteristic (ROC) curves for the logistic regression model 2 (LR2), Assessment of Different NEoplasias in the AdneXa (ADNEX) model and Risk of Malignancy Index (RMI) with ROC points for the Simple Rules superimposed. The results were obtained using pooled data (n = 2403) from IOTA phase 3.

Mentions: The currently available diagnostic tests used for the characterisation of adnexal tumours focus on the presence or absence of cancer. However, optimal patient management also depends on recognising the specific histopathological diagnosis in both benign and malignant conditions (Van Calster et al., 2014). Predicting the specific histopathology of an adnexal mass can lead to avoidance of unnecessary surgery on physiological haemorrhagic cysts, or referral to an appropriate specialist surgeon for an endometrioma (Sayasneh et al., 2014). For malignant disease, knowledge of the specific pathology of a lesion may also be critical. For example the need to thoroughly inspect the intestines and perform an appendectomy if a mucinous borderline ovarian tumour (BOT) is predicted (Sayasneh et al., 2014). In IOTA phase 4 we have already shown that clinicians with variable training backgrounds and levels of expertise find it difficult to provide a specific histological diagnosis when using their subjective assessment, especially when discriminating between certain subtypes of malignant disease (BOT, early stage invasive ovarian cancer, and metastatic disease). In this thesis we describe the development and validation of a multiclass risk prediction model ADNEX (Assessment of Different NEoplasias in the AdneXa) using data from IOTA phase 1 to 3 (Van Calster et al., 2014). This polytomous approach to adnexal tumour diagnosis is novel, since established tests like IOTA LR2 or SR only discriminate between cancer and benign conditions. The ADNEX model offered fair to excellent discrimination (AUCs ranging from 0.71 to 0.95) between four different types of ovarian malignancy (BOT, early stage I invasive ovarian cancer, stage II-IV invasive ovarian cancer, and secondary tumours metastasising to the ovaries (i.e. breast, gastro-intestinal tumours, etc)) using risk estimates (Van Calster et al., 2014). Of particular importance is the ability of ADNEX to identify stage I cancer, which the model can discriminate very well from benign tumours and advanced stage cancer and fairly well from BOT and secondary metastatic cancers. On the other hand ADNEX has similar accuracy to IOTA LR2 and SR when validated on IOTA phase 3 data for simple dichotomous risk prediction (benign versus malignant) (Fig. 3) (Testa et al., 2014; Van Calster et al., 2014). ADNEX (AUC 0.94) also performed significantly better than RMI (AUC 0.88) (Timmerman et al., 2014a; Van Calster et al., 2014).


Towards an evidence-based approach for diagnosis and management of adnexal masses: findings of the International Ovarian Tumour Analysis (IOTA) studies.

Kaijser J - Facts Views Vis Obgyn (2015)

Receiver operating characteristic (ROC) curves for the logistic regression model 2 (LR2), Assessment of Different NEoplasias in the AdneXa (ADNEX) model and Risk of Malignancy Index (RMI) with ROC points for the Simple Rules superimposed. The results were obtained using pooled data (n = 2403) from IOTA phase 3.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4402442&req=5

Figure 3: Receiver operating characteristic (ROC) curves for the logistic regression model 2 (LR2), Assessment of Different NEoplasias in the AdneXa (ADNEX) model and Risk of Malignancy Index (RMI) with ROC points for the Simple Rules superimposed. The results were obtained using pooled data (n = 2403) from IOTA phase 3.
Mentions: The currently available diagnostic tests used for the characterisation of adnexal tumours focus on the presence or absence of cancer. However, optimal patient management also depends on recognising the specific histopathological diagnosis in both benign and malignant conditions (Van Calster et al., 2014). Predicting the specific histopathology of an adnexal mass can lead to avoidance of unnecessary surgery on physiological haemorrhagic cysts, or referral to an appropriate specialist surgeon for an endometrioma (Sayasneh et al., 2014). For malignant disease, knowledge of the specific pathology of a lesion may also be critical. For example the need to thoroughly inspect the intestines and perform an appendectomy if a mucinous borderline ovarian tumour (BOT) is predicted (Sayasneh et al., 2014). In IOTA phase 4 we have already shown that clinicians with variable training backgrounds and levels of expertise find it difficult to provide a specific histological diagnosis when using their subjective assessment, especially when discriminating between certain subtypes of malignant disease (BOT, early stage invasive ovarian cancer, and metastatic disease). In this thesis we describe the development and validation of a multiclass risk prediction model ADNEX (Assessment of Different NEoplasias in the AdneXa) using data from IOTA phase 1 to 3 (Van Calster et al., 2014). This polytomous approach to adnexal tumour diagnosis is novel, since established tests like IOTA LR2 or SR only discriminate between cancer and benign conditions. The ADNEX model offered fair to excellent discrimination (AUCs ranging from 0.71 to 0.95) between four different types of ovarian malignancy (BOT, early stage I invasive ovarian cancer, stage II-IV invasive ovarian cancer, and secondary tumours metastasising to the ovaries (i.e. breast, gastro-intestinal tumours, etc)) using risk estimates (Van Calster et al., 2014). Of particular importance is the ability of ADNEX to identify stage I cancer, which the model can discriminate very well from benign tumours and advanced stage cancer and fairly well from BOT and secondary metastatic cancers. On the other hand ADNEX has similar accuracy to IOTA LR2 and SR when validated on IOTA phase 3 data for simple dichotomous risk prediction (benign versus malignant) (Fig. 3) (Testa et al., 2014; Van Calster et al., 2014). ADNEX (AUC 0.94) also performed significantly better than RMI (AUC 0.88) (Timmerman et al., 2014a; Van Calster et al., 2014).

Bottom Line: They also offer more accurate triage compared to the existing Risk of Malignancy Index (RMI).The development of the IOTA ADNEX model represents an important step forward towards more individualised patient care in this area.The IOTA study has made significant progress in relation to the classification of adnexal masses, however what is now needed is to see if these or new diagnostic tools can assist clinicians to select patients with adnexal masses that are suitable for expectant management, and that will work in all health care settings (i.e. primary vs secondary vs tertiary care).

View Article: PubMed Central - PubMed

Affiliation: KU Leuven, Department of Development and Regeneration, Leuven, Belgium. ; Department of Obstetrics and Gynaecology, University Hospitals KU Leuven, Leuven, Belgium.

ABSTRACT
Whilst the outcomes for patients with ovarian cancer clearly benefit from centralised, comprehensive care in dedicated cancer centres, unfortunately the majority of patients still do not receive appropriate specialist treatment. Any improvement in the accuracy of current triaging and referral pathways whether using new imaging tests or biomarkers would therefore be of value in order to optimise the appropriate selection of patients for such care. An analysis of current evidence shows that such tests are now available, but still await recognition, acceptance and widespread adoption. It is therefore to be hoped that present guidance relating to the classification of ovarian masses will soon become more "evidence-based". These promising tests include the International Ovarian Tumour Analysis (IOTA) LR2 model and ultrasound-based Simple Rules (SR). Based on a comprehensive recent meta-analysis both currently offer the optimal "evidence-based" approach to discriminating between cancer and benign conditions in women with adnexal tumours needing surgery. LR2 and SR are reliable tests having been shown to maintain a high sensitivity for cancer after independent external and temporal validation by the IOTA group in the hands of examiners with various levels of ultrasound expertise. They also offer more accurate triage compared to the existing Risk of Malignancy Index (RMI). The development of the IOTA ADNEX model represents an important step forward towards more individualised patient care in this area. ADNEX is a novel test that enables the more specific subtyping of adnexal cancers (i.e. borderline, stage 1 invasive, stage II-IV invasive, and secondary metastatic malignant tumours) and shares similar levels of accuracy to IOTA LR2 and SR for basic discrimination between cancer and benign disease. The IOTA study has made significant progress in relation to the classification of adnexal masses, however what is now needed is to see if these or new diagnostic tools can assist clinicians to select patients with adnexal masses that are suitable for expectant management, and that will work in all health care settings (i.e. primary vs secondary vs tertiary care). These important themes will likely control the future agenda of the IOTA project.

No MeSH data available.


Related in: MedlinePlus