Causal Impact of Hemoglobin Levels on Global Quality of Life in Patients with Cancer

Background: Current cancer treatment strategies target the preservation and enhancement of patient quality of life. Therefore, we aimed to assess the causal impact of hemoglobin (Hb) levels on global quality of life in cancer patients. Methods: We conducted a retrospective analysis using data collected from new cancer patients. The dataset included responses to the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire, demographic, and disease-related variables. We applied the Linear Non-Gaussian Acyclic Model (LiNGAM) algorithm to identify potential causal relationships among those, and their impact on global quality of life. Furthermore, to evaluate the relative importance of Hb levels on global quality of life, we utilized a Random Forest Classifier (RFC). Results: The Random Forest Classifier (RFC) emerged as the most accurate model for classifying global quality of life scores (QL2) in our analysis. RFC analysis showed that Hb level ranked as the 10th most important feature among the 23 predictors in all patients for the global quality of life. However, the LiNGAM algorithm identified the Hb value as the most significant causal factor on global quality of life (total causal effect = 3.5) for anemic patients. Moreover, the Hb value was also a significant causal factor in patients in the “other cancers” and “stage 4” subcategories, with total causal effect figures of 2.9 and 2.5, respectively. Conclusions: This study suggests that Hb levels may exert a beneficial causal effect on global quality of life in cancer patients with anemia and among those with stage 4 disease and cancers other than breast, lung, or colorectal cancer.