open access: Identifying women with suspected ovarian cancer in primary care: derivation and validation of algorithm | BMJ (note reference to recent NICE guidelines)

Objective
To derive and validate an algorithm to estimate the absolute risk of having ovarian cancer in women with and without symptoms.

Main outcome
The primary outcome was incident diagnosis of ovarian cancer recorded in the next two years.

Conclusion
The algorithm has good discrimination and calibration and, after independent validation in an external cohort, could potentially be used to identify those at highest risk of ovarian cancer to facilitate early referral and investigation. Further research is needed to assess how best to implement the algorithm, its cost effectiveness, and whether, on implementation, it has any impact on health outcomes.

.......As there are few established risk factors, targeted screening of asymptomatic patients at risk of developing ovarian cancer is unlikely to be cost effective at present (although further information is likely to become available when the UK ovarian cancer screening trial reports in 2015-6). The challenge presented by ovarian cancer, therefore, is to make the correct diagnosis as early as possible, despite the non-specific nature of symptoms and signs.4 This is particularly the case in primary care, where general practitioners need to differentiate those patients for whom further investigation is warranted from those who require reassurance or a “watch and wait” policy. Moreover, primary care clinicians need to decide which patients require urgent investigation or referral and which require routine tests or referral.........

Summary of key findings

We have developed and validated a new algorithm designed to estimate the absolute risk of having existing but as yet undiagnosed ovarian cancer based on a combination of symptoms and simple variables such as age and family history of ovarian cancer, which the patient is likely to know and which will increase the baseline absolute risk.....
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What is already known on this topic

• Ovarian cancer is the second most common gynaecological cancer and most women are diagnosed with late stage disease, which has a poor survival rate
• Earlier diagnosis could improve with more targeted investigation of symptomatic patients and increased public awareness of symptoms, which is a major challenge given the non-specific nature of some of the symptoms

What this study adds

• An algorithm based on simple clinical variables such as age, family history of ovarian cancer, anaemia, abdominal pain, abdominal distension, rectal bleeding, postmenopausal bleeding, appetite loss, and weight loss, which the patient is likely to know or which are routinely recorded in general practice computer systems, can estimate absolute risk of ovarian cancer in women with and without symptoms in primary care
• The algorithm could be integrated into general practice clinical computer systems and used to assess risk in women presenting with and without symptoms