Cancer and Diabetes: Predictive Factors in Patients with Metabolic Syndrome

Association Between Risk Factors and Major Cancers: Explainable Machine Learning Approach

Background

Cancer is a life-threatening disease and a leading cause of death worldwide, with an estimated 611,000 deaths and over 2 million new cases in the United States in 2024. The rising incidence of major cancers, including among younger individuals, highlights the need for early screening and monitoring of risk factors to manage and decrease cancer risk.

Objective

This study aimed to leverage explainable machine learning models to identify and analyze the key risk factors associated with breast, colorectal, lung, and prostate cancers. By uncovering significant associations between risk factors and these major cancer types, we sought to enhance the understanding of cancer diagnosis risk profiles. Our goal was to facilitate more precise screening, early detection, and personalized prevention strategies, ultimately contributing to better patient outcomes and promoting health equity.

Methods

Deidentified electronic health record data from Medical Information Mart for Intensive Care (MIMIC)-III was used to identify patients with 4 types of cancer who had longitudinal hospital visits prior to their diagnosis presence. Their records were matched and combined with those of patients without cancer diagnoses using propensity scores based on demographic factors. Three advanced models, penalized logistic regression, random forest, and multilayer perceptron (MLP), were conducted to identify the rank of risk factors for each cancer type, with feature importance analysis for random forest and MLP models. The rank biased overlap was adopted to compare the similarity of ranked risk factors across cancer types.

Results

Our framework evaluated the prediction performance of explainable machine learning models, with the MLP model demonstrating the best performance. It achieved an area under the receiver operating characteristic curve of 0.78 for breast cancer (n=58), 0.76 for colorectal cancer (n=140), 0.84 for lung cancer (n=398), and 0.78 for prostate cancer (n=104), outperforming other baseline models (P<.001). In addition to demographic risk factors, the most prominent nontraditional risk factors overlapped across models and cancer types, including hyperlipidemia (odds ratio [OR] 1.14, 95% CI 1.11-1.17; P<.01), diabetes (OR 1.34, 95% CI 1.29-1.39; P<.01), depressive disorders (OR 1.11, 95% CI 1.06-1.16; P<.01), heart diseases (OR 1.42, 95% CI 1.32-1.52; P<.01), and anemia (OR 1.22, 95% CI 1.14-1.30; P<.01). The similarity analysis indicated the unique risk factor pattern for lung cancer from other cancer types.

Conclusions

The study's findings demonstrated the effectiveness of explainable ML models in assessing nontraditional risk factors for major cancers and highlighted the importance of considering unique risk profiles for different cancer types. Moreover, this research served as a hypothesis-generating foundation, providing preliminary results for future investigation into cancer diagnosis risk analysis and management. Furthermore, expanding collaboration with clinical experts for external validation would be essential to refine model outputs, integrate findings into practice, and enhance their impact on patient care and cancer prevention efforts.

Improvement of Physical Functions in Elderly Patients with Heart Failure Depends on the Hepatic Reserve

OBJECTIVES

In recent years, the number of elderly heart failure patients with multiorgan failure has been increasing. Furthermore, the combination of heart failure and decreased hepatic reserve can cause severe skeletal muscle impairment and decreased survival rates. This study investigated whether the degree of improvement in the five repetitions of sit-to-stand (5STS) and walking speed (WS) differs depending on hepatic reserve in elderly heart failure patients.

METHODS

The patients were divided into the following two groups: good hepatic reserve (albumin-bilirubin score [ALBI score] ≤-2.25) and poor hepatic reserve (ALBI score >-2.25). Propensity score matching was performed using the brain natriuretic peptide level. A two-way analysis of variance (ANOVA) was performed to examine the main effects of the hepatic reserve and time points (admission or discharge).

RESULTS

After propensity score matching, 28 out of the 33 (84.8%) patients in the good hepatic reserve (age, 83.74 ± 9.25 years and ALBI score, -2.55 ± 0.19 points) and 27 out of 40 (67.5%)patients in the poor hepatic reserve (age, 85.85 ± 7.53 years and ALBI score, -1.93 ± 0.26 points) were analyzed. Two-way ANOVA showed that the 5STS (p = 0.04) and WS (p = 0.01) in poor hepatic reserve tended to be worse than in good hepatic reserve. Furthermore, the 5STS (p = 0.04) and WS tended to improve at discharge in both groups. However, the improvement in WS was not significant (p = 0.15).

CONCLUSIONS

Our study suggests that the hepatic reserve in elderly heart failure patients may be an important factor in the assessment of physical functions.

Putative Molecular Mechanisms Underpinning the Inverse Roles of Mitochondrial Respiration and Heme Function in Lung Cancer and Alzheimer's Disease

Mitochondria are the powerhouse of the cell. Mitochondria serve as the major source of oxidative stress. Impaired mitochondria produce less adenosine triphosphate (ATP) but generate more reactive oxygen species (ROS), which could be a major factor in the oxidative imbalance observed in Alzheimer's disease (AD). Well-balanced mitochondrial respiration is important for the proper functioning of cells and human health. Indeed, recent research has shown that elevated mitochondrial respiration underlies the development and therapy resistance of many types of cancer, whereas diminished mitochondrial respiration is linked to the pathogenesis of AD. Mitochondria govern several activities that are known to be changed in lung cancer, the largest cause of cancer-related mortality worldwide. Because of the significant dependence of lung cancer cells on mitochondrial respiration, numerous studies demonstrated that blocking mitochondrial activity is a potent strategy to treat lung cancer. Heme is a central factor in mitochondrial respiration/oxidative phosphorylation (OXPHOS), and its association with cancer is the subject of increased research in recent years. In neural cells, heme is a key component in mitochondrial respiration and the production of ATP. Here, we review the role of impaired heme metabolism in the etiology of AD. We discuss the numerous mitochondrial effects that may contribute to AD and cancer. In addition to emphasizing the significance of heme in the development of both AD and cancer, this review also identifies some possible biological connections between the development of the two diseases. This review explores shared biological mechanisms (Pin1, Wnt, and p53 signaling) in cancer and AD. In cancer, these mechanisms drive cell proliferation and tumorigenic functions, while in AD, they lead to cell death. Understanding these mechanisms may help advance treatments for both conditions. This review discusses precise information regarding common risk factors, such as aging, obesity, diabetes, and tobacco usage.

Lung cancer and type 2 diabetes experience in Dolj County (southwest region of Romania) - a clinical, bioclinical and pathological study

BACKGROUND AND AIM

Type 2 diabetes (T2D) and cancer, the most important public health problems nowadays, and the mechanisms between the presence of diabetes and the development of malignancies remain unclear. The leading cause of cancer death in 2020 is attributed to lung cancer. This study aimed to highlight the impact of the association of these two diseases and the predominant histopathological type of lung cancer in the selected group, glycemic imbalance, and information about the course and outlook for these patients.

PATIENTS, MATERIALS AND METHODS

The authors proposed a case-control 10-year period study, between 2007 and 2017, of two groups of patients diagnosed with T2D and lung cancer who underwent hospitalization at the Clinic of Medical Oncology, Emergency County Hospital, Craiova, Romania.

RESULTS

Our study showed a higher incidence of lung adenocarcinoma in patients diagnosed with T2D. The inflammatory syndrome is more pronounced in the diabetic group, which is supported by correlations between lactate dehydrogenase (LDH), albumin, and hemoglobin levels.

CONCLUSIONS

The duration of cancer treatment in lung cancer and the survival rate is strongly influenced by the presence of diabetes as a concomitant disease.