AI Article Synopsis

  • Ovarian cancer is the sixth most common cancer among women in the UK, making early diagnosis challenging, and risk-scoring can aid in referring patients to specialist care.
  • A systematic review analyzed 51 diagnostic cohort studies, revealing that the Risk of Ovarian Malignancy Algorithm (ROMA) score did not outperform the Risk of Malignancy Index 1 (RMI 1) and was less reliable in certain cases.
  • The findings suggest that achieving comparable sensitivity to more established models requires setting a very low threshold for RMI 1, but it would result in a significant number of false positives.

Article 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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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6139475PMC
http://dx.doi.org/10.3310/hta22440DOI Listing

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