Multifactorial Analysis of Influences on Quality of Life in Cancer Patients
View abstract on PubMed
Summary
This summary is machine-generated.Cancer patients
Area Of Science
- Oncology
- Quality of Life Research
- Health Services Research
Background
- Cancer significantly impacts patient quality of life (QOL) during and after treatment.
- QOL assessments are underutilized, and influencing factors remain poorly understood.
- A multifactorial analysis is crucial for understanding QOL in cancer patients.
Purpose Of The Study
- To identify key factors influencing the quality of life in cancer patients.
- To conduct a comprehensive multifactorial analysis of QOL determinants.
- To inform holistic patient care strategies.
Main Methods
- A cohort of 108 cancer patients participated in the study.
- Utilized the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30) and EORTC QLQ-INFO 25.
- Collected data on disease course, lifestyle, and nutritional information seeking behaviors.
Main Results
- Significant QOL differences observed based on gender, nutritional information seeking, dietitian consultation, and food intake.
- Stepwise multiple regression identified key QOL predictors: nutritional information seeking, reduced food intake, nutrition support type, age, gender, dietitian consultation, residence, and education.
- Sociodemographic and disease-related factors also influence QOL.
Conclusions
- Patient-reported need for nutritional information and dietitian consultation are significant QOL factors.
- Sociodemographic variables, cancer characteristics, and lifestyle choices collectively impact QOL.
- A holistic approach incorporating these factors is essential for optimizing cancer patient care and well-being.
Related Concept Videos
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
The factors influencing the health-illness continuum can be internal or external and may or may not be under conscious control. They are related to the following eight human dimensions, and each dimension is interrelated to one other.
• The Physical Dimension: Age, developmental stage, race, and gender fall within the physical dimension. The individual's health state and lifestyle choices are significantly influenced by these factors and include caring for the body to stay healthy...
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
When a person's physical, emotional, intellectual, social development or spiritual functioning is compromised, this deviation from a healthy normal state is called illness. Illness creates stress that in turn harms individuals. Irritation, anger, denial, hopelessness, and fear are behavioral and emotional changes an individual experiences in the phases of illness. A variety of factors influence a person's health and well-being.
For instance, risk factors are connected to illness,...
Factorial Analysis is an experimental design that applies Analysis of Variance (ANOVA) statistical procedures to examine a change in a dependent variable due to more than one independent variable, also known as factors. Changes in worker productivity can be reasoned, for example, to be influenced by salary and other conditions, such as skill level. One way to test this hypothesis is by categorizing salary into three levels (low, moderate, and high) and skills sets into two levels (entry level...
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...

