Internal and emergency medicine
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To date, we do not know if the excess of the body mass index (BMI) improves or worsens the outcomes in colorectal cancer treatment, and the correlation between BMI and prognosis remains unclear. A recent study in vitro showed a significant negative correlation between BMI and Cetuximab-induced antibody-dependent cellular cytotoxicity. On these bases, we tried to analyze the potential correlation between BMI and survival in patients affected by metastatic colorectal cancer (mCRC) and treated with Cetuximab. ⋯ No correlation between BMI and treatment response was seen between BMI ≥ 25 and BMI ≤ 24 groups (p = 0.14). Our experience suggests that mild obese and overweight patients treated with Cetuximab could experience a better survival. We also observed that among normal weight, overweight, and mild obese patients, there is a better response to immunochemotherapy in comparison with underweight patients, but this difference does not reach a significative statistical value.
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ML algorithms are used to develop prognostic and diagnostic models and so to support clinical decision-making. This study uses eight supervised ML algorithms to predict the need for intensive care, intubation, and mortality risk for COVID-19 patients. ⋯ The findings revealed that the features of C-reactive protein, the ratio of lymphocytes, lactic acid, and serum calcium have a substantial impact on COVID-19 prognostic predictions. This study provides evidence of the value of tree-based supervised ML algorithms for predicting prognosis in health care.