Researchers investigate ways of improving the diagnosis of ovarian cancer
In its latest Croakey update, the Primary Health Care Research and Information Service (better known as PHC RIS) reports on efforts to improve the diagnosis of ovarian cancer in primary care.
Working to improve the diagnosis of ovarian cancer
Amanda Carne writes:
Each year in February, Ovarian Cancer Australia runs a national Ovarian Cancer Awareness Month campaign to highlight the symptoms of ovarian cancer and to raise funds for their programs.
They report that only 40% of women with ovarian cancer will be alive five years after advanced stage diagnosis, but if ovarian cancer is diagnosed in its early stages, the chances of being well after five years doubles to 80%. In Australia, three women are diagnosed with ovarian cancer every day.
As the second most common gynaecological cancer, it has a poor survival rate and most women are diagnosed too late because of the non-specific symptoms.
Contrary to popular belief, the Pap smear test does not detect ovarian cancer. Since there is no early detection test available for ovarian cancer, it makes sense to improve referral rates for early and correct diagnosis.
In a timely cohort study (UK) of women aged 30‑84 without a diagnosis of ovarian cancer at baseline, Hippisley-Cox and Coupland aimed to derive and validate an algorithm to estimate the absolute risk of having ovarian cancer in women with and without symptoms.
The authors discovered that age, family history, anaemia, abdominal pain, abdominal distension, rectal bleeding, postmenopausal bleeding, appetite loss and weight loss are good independent predictors of ovarian cancer.
The algorithm explained 57.6% of the variation and was found to have good discrimination and calibration.
After independent validation in an external cohort, Hippisley-Cox and Coupland suggest that the algorithm could potentially be used in primary care settings to identify those at highest risk of developing ovarian cancer and to facilitate early referral and investigation.
Primary care clinicians need to decide which patients require urgent investigation or referral and which ones require routine tests or referral.
Therefore, the challenge is to make the correct diagnosis as early as possible, despite the non-specific nature of the symptoms and signs, and this algorithm may assist with this.
However, further research is needed to assess how best to implement the algorithm, its cost-effectiveness, and whether, after implementation, it has any impact on the stage of ovarian cancer at diagnosis and subsequent survival.
But it is a promising approach to improving the detection rates and prognosis of this serious disease.
• Amanda Carne is Research Associate with the Primary Health Care Research & Information Service (PHC RIS)
Hippisley-Cox J & Coupland C (2012). Identifying women with suspected ovarian cancer in primary care: derivation and validation of algorithm. BMJ, 344: d8009
This article, which can be accessed at http://www.bmj.com/content/344/bmj.d8009, features in the 1 March 2012 edition of PHC RIS eBulletin, available at http://www.phcris.org.au/publications/ebulletin/index.php.
The eBulletin is designed to inform readers of recently published articles and reports, news items, media releases, upcoming conferences and courses, research grants, scholarships and fellowships, PHC RIS products and services and relevant websites in the primary health care field. Those interested in receiving the weekly eBulletin are invited to subscribe to the free service at http://www.phcris.org.au/mailinglists/index.php
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