Official websites use. Share sensitive information only on official, secure websites. Historically, the treatment of choice for anal cancer had been abdominoperineal resection APR.
The aim of this study was to evaluate the outcomes after radical chemoradiotherapy CRT , prognostic and predictive factors and patterns of failure. This study included 47 patients treated with radical CRT for patohistologicaly confirmed anal squamous cell carcinoma. Analysed haematological parameters included: neutrophil-to-lymphocyte ratio NLR , platelet-to-lymphocyte ratio PLR , and haemoglobin level. The final logistic regression model included treatment break period. Tumour response was assessed at 24 weeks from CRT completion.
Follow-up was performed every 3 months during the first two years, and every 6 months thereafter. A complete clinical response CR was detected in 30 patients Patients who did not achieve a 6-months CR and those who had a CR after 6 months but then relapsed were referred to surgical treatment. Important prognostic factors associated with CR were baseline haemoglobin level and period of treatment interruptions. Potential haematological prognostic factors could be PLR and NLR, which can be routinely determined by low-cost and minimally invasive methods.
The anal cancer is a rare malignancy in the general population globally. According to the latest official reports from , it represented only 0. This might be related to an increased spread of human papilloma virus HPV and human immunodeficiency virus HIV through sexual transmission, which are established risk factors of this.
Historically, the treatment of choice for the anal cancer had been abdominoperineal resection APR. The optimal total dose, schedule of RT and radiation delivery techniques for the anal cancer continue to be evaluated. Current state-of-the-art does not provide uniform recommendations regarding the mentioned RT parameters. The aim of this study was to evaluate the outcomes after radical CRT for patients with anal squamous cell cancer, and to investigate prognostic and predictive factors using the logistic regression model, as well as patterns of failure.
