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

Marie Westwood*, Bram Ramaekers, Shona Lang, Sabine Grimm, Sohan Deshpande, Shelley de Kock, Nigel Armstrong, Manuela Joore, Jos Kleijnen

*Corresponding author for this work

Research output: Contribution to journal(Systematic) Review article peer-review

19 Citations (Web of Science)

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) pound. The IOTA group's simple ultrasound rules (inconclusive, assumed to be malignant) were the cheapest (5667) pound and the second most effective [16.954 LYs, 13.841 QALYs], dominating RMI 1. The ADNEX model (threshold of 10%), costing 5699 pound, 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 pound per QALY gained. At thresholds of up to 15,304 pound 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.
Original languageEnglish
Pages (from-to)1-266
Number of pages266
JournalHealth Technology Assessment
Volume22
Issue number44
DOIs
Publication statusPublished - 1 Aug 2018

Keywords

  • MALIGNANCY ALGORITHM ROMA
  • IOTA SIMPLE RULES
  • MULTICENTER EXTERNAL VALIDATION
  • ULTRASOUND-BASED RULES
  • ADNEXAL MASSES
  • PELVIC MASS
  • DIAGNOSTIC-ACCURACY
  • INDEX RMI
  • PREOPERATIVE DIAGNOSIS
  • POSTMENOPAUSAL WOMEN
  • DIFFERENTIAL-DIAGNOSIS
  • POSTOPERATIVE MORTALITY
  • MENOPAUSAL STATUS

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