Literature DB >> 30165935

Risk scores to guide referral decisions for people with suspected ovarian cancer in secondary care: a systematic review and cost-effectiveness analysis.

Marie Westwood1, Bram Ramaekers2, Shona Lang1, Sabine Grimm2, Sohan Deshpande1, Shelley de Kock1, Nigel Armstrong1, Manuela Joore2, Jos Kleijnen3.   

Abstract

BACKGROUND: Ovarian cancer is the sixth most common cancer in UK women and can be difficult to diagnose, particularly in the early stages. Risk-scoring can help to guide referral to specialist centres.
OBJECTIVES: To assess the clinical and cost-effectiveness of risk scores to guide referral decisions for women with suspected ovarian cancer in secondary care.
METHODS: Twenty-one databases, including MEDLINE and EMBASE, were searched from inception to November 2016. Review methods followed published guidelines. The meta-analysis using weighted averages and random-effects modelling was used to estimate summary sensitivity and specificity with 95% confidence intervals (CIs). The cost-effectiveness analysis considered the long-term costs and quality-adjusted life-years (QALYs) associated with different risk-scoring methods, and subsequent care pathways. Modelling comprised a decision tree and a Markov model. The decision tree was used to model short-term outcomes and the Markov model was used to estimate the long-term costs and QALYs associated with treatment and progression.
RESULTS: Fifty-one diagnostic cohort studies were included in the systematic review. The Risk of Ovarian Malignancy Algorithm (ROMA) score did not offer any advantage over the Risk of Malignancy Index 1 (RMI 1). Patients with borderline tumours or non-ovarian primaries appeared to account for disproportionately high numbers of false-negative, low-risk ROMA scores. (Confidential information has been removed.) To achieve similar levels of sensitivity to the Assessment of Different NEoplasias in the adneXa (ADNEX) model and the International Ovarian Tumour Analysis (IOTA) group's simple ultrasound rules, a very low RMI 1 decision threshold (25) would be needed; the summary sensitivity and specificity estimates for the RMI 1 at this threshold were 94.9% (95% CI 91.5% to 97.2%) and 51.1% (95% CI 47.0% to 55.2%), respectively. In the base-case analysis, RMI 1 (threshold of 250) was the least effective [16.926 life-years (LYs), 13.820 QALYs] and the second cheapest (£5669). The IOTA group's simple ultrasound rules (inconclusive, assumed to be malignant) were the cheapest (£5667) and the second most effective [16.954 LYs, 13.841 QALYs], dominating RMI 1. The ADNEX model (threshold of 10%), costing £5699, was the most effective (16.957 LYs, 13.843 QALYs), and compared with the IOTA group's simple ultrasound rules, resulted in an incremental cost-effectiveness ratio of £15,304 per QALY gained. At thresholds of up to £15,304 per QALY gained, the IOTA group's simple ultrasound rules are cost-effective; the ADNEX model (threshold of 10%) is cost-effective for higher thresholds. LIMITATIONS: Information on the downstream clinical consequences of risk-scoring was limited.
CONCLUSIONS: Both the ADNEX model and the IOTA group's simple ultrasound rules may offer increased sensitivity relative to current practice (RMI 1); that is, more women with malignant tumours would be referred to a specialist multidisciplinary team, although more women with benign tumours would also be referred. The cost-effectiveness model supports prioritisation of sensitivity over specificity. Further research is needed on the clinical consequences of risk-scoring. STUDY REGISTRATION: This study is registered as PROSPERO CRD42016053326. FUNDING DETAILS: The National Institute for Health Research Health Technology Assessment programme.

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Year:  2018        PMID: 30165935      PMCID: PMC6139475          DOI: 10.3310/hta22440

Source DB:  PubMed          Journal:  Health Technol Assess        ISSN: 1366-5278            Impact factor:   4.014


  7 in total

Review 1.  Ovarian Adnexal Reporting Data System (O-RADS) for Classifying Adnexal Masses: A Systematic Review and Meta-Analysis.

Authors:  Julio Vara; Nabil Manzour; Enrique Chacón; Ana López-Picazo; Marta Linares; Maria Ángela Pascual; Stefano Guerriero; Juan Luis Alcázar
Journal:  Cancers (Basel)       Date:  2022-06-27       Impact factor: 6.575

2.  Diagnostic Performance of Risk of Malignancy Algorithm (ROMA), Risk of Malignancy Index (RMI) and Expert Ultrasound Assessment in a Pelvic Mass Classified as Inconclusive by International Ovarian Tumour Analysis (IOTA) Simple Rules.

Authors:  Siew Fei Ngu; Yu Ka Chai; Ka Man Choi; Tsin Wah Leung; Justin Li; Gladys S T Kwok; Mandy M Y Chu; Ka Yu Tse; Vincent Y T Cheung; Hextan Y S Ngan; Karen K L Chan
Journal:  Cancers (Basel)       Date:  2022-02-05       Impact factor: 6.639

3.  Performance of the IOTA ADNEX model combined with HE4 for identifying early-stage ovarian cancer.

Authors:  Suying Yang; Jing Tang; Yue Rong; Min Wang; Jun Long; Cheng Chen; Cong Wang
Journal:  Front Oncol       Date:  2022-09-16       Impact factor: 5.738

Review 4.  ESGO/ISUOG/IOTA/ESGE Consensus Statement on pre-operative diagnosis of ovarian tumors.

Authors:  Dirk Timmerman; François Planchamp; Tom Bourne; Chiara Landolfo; Andreas du Bois; Luis Chiva; David Cibula; Nicole Concin; Daniela Fischerova; Wouter Froyman; Guillermo Gallardo Madueño; Birthe Lemley; Annika Loft; Liliana Mereu; Philippe Morice; Denis Querleu; Antonia Carla Testa; Ignace Vergote; Vincent Vandecaveye; Giovanni Scambia; Christina Fotopoulou
Journal:  Int J Gynecol Cancer       Date:  2021-06-10       Impact factor: 3.437

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

Authors:  Ben Van Calster; Lil Valentin; Wouter Froyman; Chiara Landolfo; Jolien Ceusters; Antonia C Testa; Laure Wynants; Povilas Sladkevicius; Caroline Van Holsbeke; Ekaterini Domali; Robert Fruscio; Elisabeth Epstein; Dorella Franchi; Marek J Kudla; Valentina Chiappa; Juan L Alcazar; Francesco P G Leone; Francesca Buonomo; Maria Elisabetta Coccia; Stefano Guerriero; Nandita Deo; Ligita Jokubkiene; Luca Savelli; Daniela Fischerová; Artur Czekierdowski; Jeroen Kaijser; An Coosemans; Giovanni Scambia; Ignace Vergote; Tom Bourne; Dirk Timmerman
Journal:  BMJ       Date:  2020-07-30

6.  Diagnostic Accuracy of the ADNEX Model for Ovarian Cancer at the 15% Cut-Off Value: A Systematic Review and Meta-Analysis.

Authors:  Xiaotong Huang; Ziwei Wang; Meiqin Zhang; Hong Luo
Journal:  Front Oncol       Date:  2021-06-17       Impact factor: 6.244

7.  Pelvic mass, ascites, hydrothorax: a malignant or benign condition? Meigs syndrome with high levels of CA 125.

Authors:  Guglielmo Stabile; Giulia Zinicola; Federico Romano; Antonio Simone Laganà; Chiara Dal Pozzolo; Giuseppe Ricci
Journal:  Prz Menopauzalny       Date:  2021-05-25
  7 in total

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