How the trial results emphasize the importance of cervical cancer screening
James Fleck & Guilherme Brondani: Anticancerweb 26 (01), 2019
HPV vaccination and Pap smear failures are responsible for a worldwide cervical cancer incidence of569847 cases. This data, extracted from the most recent Global Cancer Observatory (International Agency for Research on Cancer, OMS 2018), is magnified in its epidemiological impact by an unacceptable mortality of 311365 women.
Despite screening of cervical cancer being considered a category A recommendation by the US Preventive Service Task Force, this effective health policy has been overlooked in a less developed part of the world, leading to a humanitarian disaster. Recently, researchers from the Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USAidentified artificial intelligence as a simple, universal and reliable ally for a more accurate cervical cancer screening. Published in January 2019 in the Journal of National Cancer Institute, a population-based longitudinal study validated the use of digitalized uterine cervix images in the identification of premalignant lesions (CIN2 and CIN3) as well as carcinoma in situ (CIS). Tested in Costa Rica high risk women population, the new method revealed a higher accuracy (AUC = 0.91) when compared to conventional cytology of the uterine cervix (AUC = 0.71). Future widespread use of the new test might overcome presently negligence.
Unfortunately, nowadays women epidemiological data still shows cervical cancer taking the forth position both in incidence (ASR = 13.1) and mortality (ASR = 6.9) in the world. To many cases are still diagnosed as locally-advanced or metastatic disease, decreasing or preventing curative intervention. These patients are no longer candidates for surgery, being treated with a combination of radiotherapy + cisplatin (locally advanced) or chemotherapy alone (metastatic disease). Despite the efforts, there is a high incidence of recurrence, occurring in the unfavorable setting of platin-resistance.
In an attempt to improve the results of palliative treatment of women with recurrent, persistent or metastatic cervical carcinoma, the New England Journal of Medicinepublished in 2014 a factorial study 2 x 2 evaluating the addition of bevacizumab, a vascular endothelial growth factor (VEGF) monoclonal antibody to two different chemotherapy doublets (cisplatin 50 mg/m2 D1 + paclitaxel 135 – 175 mg/m2 D1 or topotecan 0.75 mg/m2 D1–D3 + paclitaxel 175 mg/m2 D1). The two alternative hypothesis were overcoming platin-resistance and blockage of angiogenesis. The GOG 240 study randomized 462 patients to both chemotherapy doublets with or without bevacizumab. An efficacy interim analysis showed equivalence in mortality rate (HR = 1.2) for the chemotherapy doublets, both in women with and without previous exposure to cisplatin. However, there was an increase of 3.7 months in the median overall survival associated with the use of bevacizumab (HR = 0.71, P = 0.004). The survival benefit was obtained at the expenses of increased toxicity (grade 2 hypertension, grade 3 thromboembolic events and grade 3 gastrointestinal fistulae). Major caveats are the low doses of both chemotherapy alone arms (mainly, cisplatin at a dose of 50 mg/m2 D1 and topotecan at a dose of 0.75 mg/m2 D1-D3) and the presumed and doubtful rationale of angiogenesis as being a central factor in late tumor progression.
Looking prospectively, public health rationality should move toward advances in screening of cervical cancer, not only because it is more cost effective, but specially because it has a higher chance to overcome this humanitarian disaster. The attached video shows the importance of Dr. Mark Schiffman team, working for more than 30 years on cervical cancer epidemiological and translation research in the Division of Cancer Epidemiology and Genetics at the national Cancer Institute, USA.
Krishnansu S. Tewari, Michael W. Sill, Harry J. Long III, et al: Improved Survival with Bevacizumab in Advanced Cervical Cancer, N Engl J Med370: 734 – 743, 2014
Liming Hu, David Bell, Sameer Antani, Zhiyun Xue, et al: An Observational Study of Deep Learning and Automated Evaluation of Cervical Images for Cancer Screening,JNCIJan, 2019