Body weight and body surface area of adult patients with selected cancers: An Italian multicenter study

Although body weight (BW) and body surface area (BSA) are utilized to establish the appropriate dosage of anticancer drugs, their distribution in cancer patients is poorly studied, making it challenging to predict the amount of drug use and related costs of BW or BAS-dosed regimens. This study investigates the distribution of BW and BSA in adults with selected cancers who initiated systemic anticancer treatment in the eastern Emilia-Romagna region hospitals between 2011 and 2021. BW and BSA were collected at the first cycle of each new treatment line, with multiple measurements for patients receiving various treatments or treating for other primary malignancies. Results were grouped by sex, tumor site and treatment setting, and the normal distribution hypothesis was tested for each group. Both linear regression model and quantile regression at the 50th, 25th and 75th percentiles were run to explore the factors influencing BSA. The analysis included 20,634 treatment lines and the corresponding BW and BSA measures from a sample of 13,036 patients. The average BW was 68.05kg (64.20kg for females and 75.07kg for males) and the average BSA was 1.76m2 (1.66m2 for females and 1.87m2 for males). In women, the highest BW was in breast and colon groups, while in men, it was associated with prostate and rectum cancers. The model indicated significant association between BSA, age, sex and tumor localization. Notably, stomach and lung cancers were linked to lower BSA for both sexes (for females -0.081 and -0.041m2 respectively compared to those with breast cancer). Advanced settings were related to lower BSA than neoadjuvant treatment, especially for stomach cancer patients, who experienced a weight loss of 3 to 6kg as therapy progressed. The regression models for predicting BSA can assist regulatory bodies in determining reimbursement for new chemotherapy drugs and help hospitals forecast drug utilization and expenditure more accurately.