Cancer experts at the US National Cancer Institute (part of the US National Institutes of Health [NIH]) are creating a tool to work out the percentage risk a woman has of developing cervical cancer. The proposal is in a Keynote Comment, published in the November edition of The Lancet Oncology, written by Dr Hormuzd A Katki, National Cancer Institute, Bethesda, MD, USA. A preliminary version of the tool is expected to be ready by the end of 2010.
Currently, screening programmes for cervical cancer usually rely on cytology as the first-line screen. Women who are found to be cytologically abnormal are triaged by carcinogenic human papillomavirus (HPV) DNA testing or by repeat cytology, or are referred directly for a colposcopic examination. At colposcopy, biopsies are taken from any apparent lesions. Treatment is decided on the basis of the combined cytological, colposcopic, and histological diagnoses during the patient’s history. These decision processes are formalised in complex consensus management algorithms that narrow down the clinical management options to a single course of action. But the authors point out that, with each new technology, algorithms become exponentially more complex.
The authors say: “Instead of providing clinicians with algorithms, we propose to provide clinicians with their patient’s risk of developing cervical cancer. As a surrogate for cervical cancer, we propose to use cervical precancer, best defined as histological cervical intraepithelial neoplasia grade 3 (CIN3) or more severe (CIN3+), or less precisely by CIN2+, a common treatment threshold.”
Clinical trials are generating vast volumes of data on risk of cervical precancer, which can be calculated at the time of screening, for women sent immediately to colposcopy, or at 1-year, 2-year, or 3-year follow-up intervals, as desired. The authors say: “The risk of cervical precancer is a unifying concept to guide management, regardless of which combination of tests a woman has undergone, because risk of cervical precancer boils down a complex battery of test results over time into a single percentage that forms a basis for action.”
As an example, the authors suggest possible cases of high and low risk. A 33-year-old woman, HPV- and cytology-negative—might be reassured, based on the risk calculation, that their 5-year risk of CIN3+ is less than 1%. But the highest-risk women (eg, 33-years-old, persistent HPV-16, high-grade cytology, high-grade colposcopic impression) might have a greater than 80% 5-year risk, and might be advised to have surgery to remove the lesions, even if biopsy confirmation is absent.
The authors say: “In clinical practice, the risk percentage can be computed using an application run on a computer or personal digital assistant (PDA) after entering the patient’s age, current test results, and (if available) past test results. The output will probably include the current precancer risk and future precancer risks 1, 3, and 5 years in the future. Clinicians or their assistants could use the tool to compute these risks before patient visits, and keep track of risk estimates over time in medical records.”
They conclude: “Unlike all other cancers, cervical precancer is predictable with unprecedented accuracy and power because we can test for its necessary cause (HPV), a precancerous lesion has been defined (CIN3+), and we can readily access the cervix for screening and effective treatment. As a result, more is known about the natural history of cervical lesions than any other cancer, and a risk tool can exploit this knowledge. As biomarkers for the causes and precancerous states of other cancers are discovered and developed into clinical tests, other cancers will one day be ready for large-scale prevention programmes based on risk management. Cervical cancer prevention through risk estimation will be the paradigm for the rational, effective, and cost-effective way to prevent cancer.”
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